{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "@author = Ali Masoumnia\n",
    "\n",
    "amasoumnia@outlook.com\n",
    "\n",
    "# H&T Fortune Challenge\n",
    "\n",
    "## Introduction\n",
    "\n",
    "A minimum spanning tree is an acylical subset of an undirected graph where the sum of all weights is kept at a full minimum, while the tree still spans the graph. In this implementation, an undirected weighted graph is represented by an adjacency matrix and is both input and output of the mst function. Pandas dataframes are used for these matrices to facilitate the string indicies of tickers as nodes. The pseudocode for this function is presented in: https://arxiv.org/abs/1703.00485."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Minimum Spanning Tree\n",
    "\n",
    "### Kruskal Implementation\n",
    "#### Data Handling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "#function written for pandas adjacency matrices\n",
    "from kruskal import mst\n",
    "from tests import check_mst"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"amex_rand50.csv\", parse_dates=True, index_col='date')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Computing log Returns of the Assets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DF</th>\n",
       "      <th>SQBG</th>\n",
       "      <th>C</th>\n",
       "      <th>PPC</th>\n",
       "      <th>VOD</th>\n",
       "      <th>TRUP</th>\n",
       "      <th>NATI</th>\n",
       "      <th>GNUS</th>\n",
       "      <th>RINF</th>\n",
       "      <th>DMLP</th>\n",
       "      <th>...</th>\n",
       "      <th>GER</th>\n",
       "      <th>DVYE</th>\n",
       "      <th>GAM</th>\n",
       "      <th>AY</th>\n",
       "      <th>LAC</th>\n",
       "      <th>NKSH</th>\n",
       "      <th>EME</th>\n",
       "      <th>BBDO</th>\n",
       "      <th>GRIF</th>\n",
       "      <th>IMGN</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2015-05-01</th>\n",
       "      <td>0.003685</td>\n",
       "      <td>-0.010539</td>\n",
       "      <td>0.008218</td>\n",
       "      <td>0.029519</td>\n",
       "      <td>-0.007700</td>\n",
       "      <td>0.043571</td>\n",
       "      <td>-0.008427</td>\n",
       "      <td>-0.060432</td>\n",
       "      <td>0.007277</td>\n",
       "      <td>0.001747</td>\n",
       "      <td>...</td>\n",
       "      <td>0.009744</td>\n",
       "      <td>0.002631</td>\n",
       "      <td>0.009321</td>\n",
       "      <td>-0.011269</td>\n",
       "      <td>-0.049597</td>\n",
       "      <td>-0.003453</td>\n",
       "      <td>0.015783</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.014406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-05-04</th>\n",
       "      <td>-0.004301</td>\n",
       "      <td>-0.013126</td>\n",
       "      <td>0.007598</td>\n",
       "      <td>0.001963</td>\n",
       "      <td>0.002859</td>\n",
       "      <td>0.021726</td>\n",
       "      <td>0.005976</td>\n",
       "      <td>-0.013201</td>\n",
       "      <td>-0.008866</td>\n",
       "      <td>-0.005249</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.006485</td>\n",
       "      <td>0.010239</td>\n",
       "      <td>0.003088</td>\n",
       "      <td>0.015389</td>\n",
       "      <td>0.016807</td>\n",
       "      <td>0.002073</td>\n",
       "      <td>0.003742</td>\n",
       "      <td>-0.022990</td>\n",
       "      <td>0.027718</td>\n",
       "      <td>0.003569</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-05-05</th>\n",
       "      <td>-0.009901</td>\n",
       "      <td>-0.008292</td>\n",
       "      <td>-0.015253</td>\n",
       "      <td>-0.012633</td>\n",
       "      <td>-0.008025</td>\n",
       "      <td>0.008811</td>\n",
       "      <td>0.006986</td>\n",
       "      <td>0.039093</td>\n",
       "      <td>0.001589</td>\n",
       "      <td>0.008734</td>\n",
       "      <td>...</td>\n",
       "      <td>0.008422</td>\n",
       "      <td>0.004541</td>\n",
       "      <td>-0.010424</td>\n",
       "      <td>0.002054</td>\n",
       "      <td>0.016529</td>\n",
       "      <td>-0.019168</td>\n",
       "      <td>0.002195</td>\n",
       "      <td>-0.021548</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.035049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-05-06</th>\n",
       "      <td>-0.006238</td>\n",
       "      <td>0.009117</td>\n",
       "      <td>-0.009984</td>\n",
       "      <td>-0.028614</td>\n",
       "      <td>0.014853</td>\n",
       "      <td>0.007491</td>\n",
       "      <td>-0.011201</td>\n",
       "      <td>-0.039093</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.008227</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.011681</td>\n",
       "      <td>-0.005625</td>\n",
       "      <td>-0.005965</td>\n",
       "      <td>-0.017145</td>\n",
       "      <td>0.048009</td>\n",
       "      <td>-0.005646</td>\n",
       "      <td>0.006556</td>\n",
       "      <td>-0.004963</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.011132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-05-07</th>\n",
       "      <td>-0.003762</td>\n",
       "      <td>0.032470</td>\n",
       "      <td>0.009234</td>\n",
       "      <td>-0.005329</td>\n",
       "      <td>-0.001419</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.000704</td>\n",
       "      <td>-0.037229</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.010839</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.004580</td>\n",
       "      <td>-0.006967</td>\n",
       "      <td>0.003697</td>\n",
       "      <td>0.018609</td>\n",
       "      <td>-0.015748</td>\n",
       "      <td>-0.002480</td>\n",
       "      <td>-0.007433</td>\n",
       "      <td>0.016774</td>\n",
       "      <td>0.000311</td>\n",
       "      <td>0.024571</td>\n",
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       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>2019-04-12</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.094491</td>\n",
       "      <td>0.022651</td>\n",
       "      <td>0.019123</td>\n",
       "      <td>0.014278</td>\n",
       "      <td>-0.009586</td>\n",
       "      <td>0.019032</td>\n",
       "      <td>0.041243</td>\n",
       "      <td>0.005751</td>\n",
       "      <td>0.020308</td>\n",
       "      <td>...</td>\n",
       "      <td>0.015748</td>\n",
       "      <td>0.005371</td>\n",
       "      <td>0.000878</td>\n",
       "      <td>0.003982</td>\n",
       "      <td>0.010953</td>\n",
       "      <td>-0.007737</td>\n",
       "      <td>0.006942</td>\n",
       "      <td>-0.015326</td>\n",
       "      <td>0.016584</td>\n",
       "      <td>-0.014815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-04-15</th>\n",
       "      <td>0.072103</td>\n",
       "      <td>0.017858</td>\n",
       "      <td>-0.000593</td>\n",
       "      <td>0.019609</td>\n",
       "      <td>0.014615</td>\n",
       "      <td>0.005368</td>\n",
       "      <td>-0.007015</td>\n",
       "      <td>0.005038</td>\n",
       "      <td>-0.000358</td>\n",
       "      <td>-0.007762</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.017514</td>\n",
       "      <td>0.002918</td>\n",
       "      <td>0.005252</td>\n",
       "      <td>0.001985</td>\n",
       "      <td>-0.017583</td>\n",
       "      <td>0.000970</td>\n",
       "      <td>0.002086</td>\n",
       "      <td>0.001286</td>\n",
       "      <td>0.007918</td>\n",
       "      <td>0.022141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-04-16</th>\n",
       "      <td>-0.090972</td>\n",
       "      <td>0.008811</td>\n",
       "      <td>0.028241</td>\n",
       "      <td>0.029530</td>\n",
       "      <td>-0.001075</td>\n",
       "      <td>-0.022511</td>\n",
       "      <td>0.006803</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.000717</td>\n",
       "      <td>0.002076</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.012445</td>\n",
       "      <td>0.001940</td>\n",
       "      <td>0.003486</td>\n",
       "      <td>-0.001985</td>\n",
       "      <td>-0.054683</td>\n",
       "      <td>-0.014656</td>\n",
       "      <td>0.000391</td>\n",
       "      <td>0.003849</td>\n",
       "      <td>-0.007096</td>\n",
       "      <td>-0.011009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-04-17</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.203599</td>\n",
       "      <td>0.014894</td>\n",
       "      <td>0.053852</td>\n",
       "      <td>0.006434</td>\n",
       "      <td>-0.032511</td>\n",
       "      <td>-0.013867</td>\n",
       "      <td>-0.005038</td>\n",
       "      <td>0.002151</td>\n",
       "      <td>-0.003115</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.012601</td>\n",
       "      <td>0.001695</td>\n",
       "      <td>0.002028</td>\n",
       "      <td>-0.006479</td>\n",
       "      <td>-0.047971</td>\n",
       "      <td>0.027904</td>\n",
       "      <td>0.002211</td>\n",
       "      <td>-0.029892</td>\n",
       "      <td>-0.000274</td>\n",
       "      <td>-0.068729</td>\n",
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       "    <tr>\n",
       "      <th>2019-04-18</th>\n",
       "      <td>0.009479</td>\n",
       "      <td>0.042112</td>\n",
       "      <td>-0.009713</td>\n",
       "      <td>0.002715</td>\n",
       "      <td>-0.010207</td>\n",
       "      <td>-0.011679</td>\n",
       "      <td>0.008343</td>\n",
       "      <td>0.005038</td>\n",
       "      <td>0.002503</td>\n",
       "      <td>-0.003647</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.009099</td>\n",
       "      <td>0.000484</td>\n",
       "      <td>0.002313</td>\n",
       "      <td>0.007968</td>\n",
       "      <td>-0.014852</td>\n",
       "      <td>0.000478</td>\n",
       "      <td>0.033096</td>\n",
       "      <td>0.019596</td>\n",
       "      <td>0.005737</td>\n",
       "      <td>-0.028058</td>\n",
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      "text/plain": [
       "                  DF      SQBG         C       PPC       VOD      TRUP  \\\n",
       "date                                                                     \n",
       "2015-05-01  0.003685 -0.010539  0.008218  0.029519 -0.007700  0.043571   \n",
       "2015-05-04 -0.004301 -0.013126  0.007598  0.001963  0.002859  0.021726   \n",
       "2015-05-05 -0.009901 -0.008292 -0.015253 -0.012633 -0.008025  0.008811   \n",
       "2015-05-06 -0.006238  0.009117 -0.009984 -0.028614  0.014853  0.007491   \n",
       "2015-05-07 -0.003762  0.032470  0.009234 -0.005329 -0.001419  0.000000   \n",
       "...              ...       ...       ...       ...       ...       ...   \n",
       "2019-04-12  0.000000 -0.094491  0.022651  0.019123  0.014278 -0.009586   \n",
       "2019-04-15  0.072103  0.017858 -0.000593  0.019609  0.014615  0.005368   \n",
       "2019-04-16 -0.090972  0.008811  0.028241  0.029530 -0.001075 -0.022511   \n",
       "2019-04-17  0.000000 -0.203599  0.014894  0.053852  0.006434 -0.032511   \n",
       "2019-04-18  0.009479  0.042112 -0.009713  0.002715 -0.010207 -0.011679   \n",
       "\n",
       "                NATI      GNUS      RINF      DMLP  ...       GER      DVYE  \\\n",
       "date                                                ...                       \n",
       "2015-05-01 -0.008427 -0.060432  0.007277  0.001747  ...  0.009744  0.002631   \n",
       "2015-05-04  0.005976 -0.013201 -0.008866 -0.005249  ... -0.006485  0.010239   \n",
       "2015-05-05  0.006986  0.039093  0.001589  0.008734  ...  0.008422  0.004541   \n",
       "2015-05-06 -0.011201 -0.039093  0.000000  0.008227  ... -0.011681 -0.005625   \n",
       "2015-05-07 -0.000704 -0.037229  0.000000 -0.010839  ... -0.004580 -0.006967   \n",
       "...              ...       ...       ...       ...  ...       ...       ...   \n",
       "2019-04-12  0.019032  0.041243  0.005751  0.020308  ...  0.015748  0.005371   \n",
       "2019-04-15 -0.007015  0.005038 -0.000358 -0.007762  ... -0.017514  0.002918   \n",
       "2019-04-16  0.006803  0.000000 -0.000717  0.002076  ... -0.012445  0.001940   \n",
       "2019-04-17 -0.013867 -0.005038  0.002151 -0.003115  ... -0.012601  0.001695   \n",
       "2019-04-18  0.008343  0.005038  0.002503 -0.003647  ... -0.009099  0.000484   \n",
       "\n",
       "                 GAM        AY       LAC      NKSH       EME      BBDO  \\\n",
       "date                                                                     \n",
       "2015-05-01  0.009321 -0.011269 -0.049597 -0.003453  0.015783  0.000000   \n",
       "2015-05-04  0.003088  0.015389  0.016807  0.002073  0.003742 -0.022990   \n",
       "2015-05-05 -0.010424  0.002054  0.016529 -0.019168  0.002195 -0.021548   \n",
       "2015-05-06 -0.005965 -0.017145  0.048009 -0.005646  0.006556 -0.004963   \n",
       "2015-05-07  0.003697  0.018609 -0.015748 -0.002480 -0.007433  0.016774   \n",
       "...              ...       ...       ...       ...       ...       ...   \n",
       "2019-04-12  0.000878  0.003982  0.010953 -0.007737  0.006942 -0.015326   \n",
       "2019-04-15  0.005252  0.001985 -0.017583  0.000970  0.002086  0.001286   \n",
       "2019-04-16  0.003486 -0.001985 -0.054683 -0.014656  0.000391  0.003849   \n",
       "2019-04-17  0.002028 -0.006479 -0.047971  0.027904  0.002211 -0.029892   \n",
       "2019-04-18  0.002313  0.007968 -0.014852  0.000478  0.033096  0.019596   \n",
       "\n",
       "                GRIF      IMGN  \n",
       "date                            \n",
       "2015-05-01  0.000000  0.014406  \n",
       "2015-05-04  0.027718  0.003569  \n",
       "2015-05-05  0.000000 -0.035049  \n",
       "2015-05-06  0.000000 -0.011132  \n",
       "2015-05-07  0.000311  0.024571  \n",
       "...              ...       ...  \n",
       "2019-04-12  0.016584 -0.014815  \n",
       "2019-04-15  0.007918  0.022141  \n",
       "2019-04-16 -0.007096 -0.011009  \n",
       "2019-04-17 -0.000274 -0.068729  \n",
       "2019-04-18  0.005737 -0.028058  \n",
       "\n",
       "[999 rows x 50 columns]"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "log_ret = np.log(df).diff().dropna()\n",
    "log_ret"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Computing the Correlation Matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DF</th>\n",
       "      <th>SQBG</th>\n",
       "      <th>C</th>\n",
       "      <th>PPC</th>\n",
       "      <th>VOD</th>\n",
       "      <th>TRUP</th>\n",
       "      <th>NATI</th>\n",
       "      <th>GNUS</th>\n",
       "      <th>RINF</th>\n",
       "      <th>DMLP</th>\n",
       "      <th>...</th>\n",
       "      <th>GER</th>\n",
       "      <th>DVYE</th>\n",
       "      <th>GAM</th>\n",
       "      <th>AY</th>\n",
       "      <th>LAC</th>\n",
       "      <th>NKSH</th>\n",
       "      <th>EME</th>\n",
       "      <th>BBDO</th>\n",
       "      <th>GRIF</th>\n",
       "      <th>IMGN</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>DF</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.134295</td>\n",
       "      <td>0.117884</td>\n",
       "      <td>0.185416</td>\n",
       "      <td>0.134690</td>\n",
       "      <td>0.072274</td>\n",
       "      <td>0.079081</td>\n",
       "      <td>0.059838</td>\n",
       "      <td>0.030613</td>\n",
       "      <td>0.082329</td>\n",
       "      <td>...</td>\n",
       "      <td>0.110893</td>\n",
       "      <td>0.095780</td>\n",
       "      <td>0.162096</td>\n",
       "      <td>0.059253</td>\n",
       "      <td>0.013526</td>\n",
       "      <td>0.123530</td>\n",
       "      <td>0.116517</td>\n",
       "      <td>0.069471</td>\n",
       "      <td>0.022214</td>\n",
       "      <td>0.045443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SQBG</th>\n",
       "      <td>0.134295</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.188575</td>\n",
       "      <td>0.073260</td>\n",
       "      <td>0.085516</td>\n",
       "      <td>0.144972</td>\n",
       "      <td>0.159547</td>\n",
       "      <td>0.086579</td>\n",
       "      <td>0.105411</td>\n",
       "      <td>0.130219</td>\n",
       "      <td>...</td>\n",
       "      <td>0.160279</td>\n",
       "      <td>0.177127</td>\n",
       "      <td>0.184769</td>\n",
       "      <td>0.115473</td>\n",
       "      <td>0.056405</td>\n",
       "      <td>0.167408</td>\n",
       "      <td>0.230055</td>\n",
       "      <td>0.113140</td>\n",
       "      <td>0.154118</td>\n",
       "      <td>0.028745</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>0.117884</td>\n",
       "      <td>0.188575</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.195809</td>\n",
       "      <td>0.401970</td>\n",
       "      <td>0.250866</td>\n",
       "      <td>0.358793</td>\n",
       "      <td>0.089070</td>\n",
       "      <td>0.207429</td>\n",
       "      <td>0.189276</td>\n",
       "      <td>...</td>\n",
       "      <td>0.423860</td>\n",
       "      <td>0.539164</td>\n",
       "      <td>0.594398</td>\n",
       "      <td>0.246211</td>\n",
       "      <td>0.189167</td>\n",
       "      <td>0.330709</td>\n",
       "      <td>0.481906</td>\n",
       "      <td>0.182026</td>\n",
       "      <td>0.143624</td>\n",
       "      <td>0.223703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PPC</th>\n",
       "      <td>0.185416</td>\n",
       "      <td>0.073260</td>\n",
       "      <td>0.195809</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.217682</td>\n",
       "      <td>0.100858</td>\n",
       "      <td>0.160136</td>\n",
       "      <td>0.047757</td>\n",
       "      <td>0.096466</td>\n",
       "      <td>0.102827</td>\n",
       "      <td>...</td>\n",
       "      <td>0.149429</td>\n",
       "      <td>0.247542</td>\n",
       "      <td>0.236449</td>\n",
       "      <td>0.136715</td>\n",
       "      <td>0.032140</td>\n",
       "      <td>0.132911</td>\n",
       "      <td>0.249026</td>\n",
       "      <td>0.132804</td>\n",
       "      <td>0.060087</td>\n",
       "      <td>0.037325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VOD</th>\n",
       "      <td>0.134690</td>\n",
       "      <td>0.085516</td>\n",
       "      <td>0.401970</td>\n",
       "      <td>0.217682</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.054646</td>\n",
       "      <td>0.224806</td>\n",
       "      <td>0.109669</td>\n",
       "      <td>0.091964</td>\n",
       "      <td>0.123914</td>\n",
       "      <td>...</td>\n",
       "      <td>0.301992</td>\n",
       "      <td>0.460423</td>\n",
       "      <td>0.400955</td>\n",
       "      <td>0.183211</td>\n",
       "      <td>0.101225</td>\n",
       "      <td>0.148344</td>\n",
       "      <td>0.255465</td>\n",
       "      <td>0.144951</td>\n",
       "      <td>0.048907</td>\n",
       "      <td>0.155452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TRUP</th>\n",
       "      <td>0.072274</td>\n",
       "      <td>0.144972</td>\n",
       "      <td>0.250866</td>\n",
       "      <td>0.100858</td>\n",
       "      <td>0.054646</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.213302</td>\n",
       "      <td>-0.004193</td>\n",
       "      <td>0.068103</td>\n",
       "      <td>0.087518</td>\n",
       "      <td>...</td>\n",
       "      <td>0.138302</td>\n",
       "      <td>0.204934</td>\n",
       "      <td>0.239660</td>\n",
       "      <td>0.145081</td>\n",
       "      <td>0.097276</td>\n",
       "      <td>0.217666</td>\n",
       "      <td>0.243584</td>\n",
       "      <td>0.068564</td>\n",
       "      <td>0.076308</td>\n",
       "      <td>0.089468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NATI</th>\n",
       "      <td>0.079081</td>\n",
       "      <td>0.159547</td>\n",
       "      <td>0.358793</td>\n",
       "      <td>0.160136</td>\n",
       "      <td>0.224806</td>\n",
       "      <td>0.213302</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.025573</td>\n",
       "      <td>0.075845</td>\n",
       "      <td>0.141107</td>\n",
       "      <td>...</td>\n",
       "      <td>0.233829</td>\n",
       "      <td>0.363862</td>\n",
       "      <td>0.396882</td>\n",
       "      <td>0.168621</td>\n",
       "      <td>0.126861</td>\n",
       "      <td>0.230386</td>\n",
       "      <td>0.403664</td>\n",
       "      <td>0.162042</td>\n",
       "      <td>0.073413</td>\n",
       "      <td>0.161721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GNUS</th>\n",
       "      <td>0.059838</td>\n",
       "      <td>0.086579</td>\n",
       "      <td>0.089070</td>\n",
       "      <td>0.047757</td>\n",
       "      <td>0.109669</td>\n",
       "      <td>-0.004193</td>\n",
       "      <td>0.025573</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.033590</td>\n",
       "      <td>0.047493</td>\n",
       "      <td>...</td>\n",
       "      <td>0.149547</td>\n",
       "      <td>0.080735</td>\n",
       "      <td>0.053558</td>\n",
       "      <td>0.063280</td>\n",
       "      <td>0.077096</td>\n",
       "      <td>0.073506</td>\n",
       "      <td>0.056087</td>\n",
       "      <td>-0.019714</td>\n",
       "      <td>0.083590</td>\n",
       "      <td>0.042534</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RINF</th>\n",
       "      <td>0.030613</td>\n",
       "      <td>0.105411</td>\n",
       "      <td>0.207429</td>\n",
       "      <td>0.096466</td>\n",
       "      <td>0.091964</td>\n",
       "      <td>0.068103</td>\n",
       "      <td>0.075845</td>\n",
       "      <td>0.033590</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.115095</td>\n",
       "      <td>...</td>\n",
       "      <td>0.209557</td>\n",
       "      <td>0.163020</td>\n",
       "      <td>0.120953</td>\n",
       "      <td>0.139755</td>\n",
       "      <td>0.110883</td>\n",
       "      <td>0.091549</td>\n",
       "      <td>0.152449</td>\n",
       "      <td>0.057738</td>\n",
       "      <td>0.020015</td>\n",
       "      <td>0.066018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DMLP</th>\n",
       "      <td>0.082329</td>\n",
       "      <td>0.130219</td>\n",
       "      <td>0.189276</td>\n",
       "      <td>0.102827</td>\n",
       "      <td>0.123914</td>\n",
       "      <td>0.087518</td>\n",
       "      <td>0.141107</td>\n",
       "      <td>0.047493</td>\n",
       "      <td>0.115095</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.384791</td>\n",
       "      <td>0.304740</td>\n",
       "      <td>0.212286</td>\n",
       "      <td>0.132744</td>\n",
       "      <td>0.101404</td>\n",
       "      <td>0.118872</td>\n",
       "      <td>0.201675</td>\n",
       "      <td>0.148910</td>\n",
       "      <td>-0.009387</td>\n",
       "      <td>0.080556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NTES</th>\n",
       "      <td>0.007202</td>\n",
       "      <td>0.038813</td>\n",
       "      <td>0.239071</td>\n",
       "      <td>0.082621</td>\n",
       "      <td>0.242499</td>\n",
       "      <td>0.100268</td>\n",
       "      <td>0.207969</td>\n",
       "      <td>0.061409</td>\n",
       "      <td>0.055390</td>\n",
       "      <td>0.060003</td>\n",
       "      <td>...</td>\n",
       "      <td>0.172861</td>\n",
       "      <td>0.399044</td>\n",
       "      <td>0.278208</td>\n",
       "      <td>0.064778</td>\n",
       "      <td>0.104337</td>\n",
       "      <td>0.065146</td>\n",
       "      <td>0.192172</td>\n",
       "      <td>0.131301</td>\n",
       "      <td>0.064507</td>\n",
       "      <td>0.144551</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EMD</th>\n",
       "      <td>0.063258</td>\n",
       "      <td>0.111098</td>\n",
       "      <td>0.267974</td>\n",
       "      <td>0.165229</td>\n",
       "      <td>0.261423</td>\n",
       "      <td>0.091863</td>\n",
       "      <td>0.146243</td>\n",
       "      <td>0.058068</td>\n",
       "      <td>0.118041</td>\n",
       "      <td>0.203802</td>\n",
       "      <td>...</td>\n",
       "      <td>0.405795</td>\n",
       "      <td>0.447581</td>\n",
       "      <td>0.398401</td>\n",
       "      <td>0.195391</td>\n",
       "      <td>0.145178</td>\n",
       "      <td>0.105937</td>\n",
       "      <td>0.198976</td>\n",
       "      <td>0.151878</td>\n",
       "      <td>0.151305</td>\n",
       "      <td>0.107066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>QMN</th>\n",
       "      <td>0.093452</td>\n",
       "      <td>0.105410</td>\n",
       "      <td>0.149722</td>\n",
       "      <td>0.094157</td>\n",
       "      <td>0.179511</td>\n",
       "      <td>0.140612</td>\n",
       "      <td>0.188852</td>\n",
       "      <td>0.101747</td>\n",
       "      <td>0.089899</td>\n",
       "      <td>0.149836</td>\n",
       "      <td>...</td>\n",
       "      <td>0.232329</td>\n",
       "      <td>0.258209</td>\n",
       "      <td>0.299926</td>\n",
       "      <td>0.154724</td>\n",
       "      <td>0.087286</td>\n",
       "      <td>0.127749</td>\n",
       "      <td>0.164366</td>\n",
       "      <td>0.123853</td>\n",
       "      <td>0.077512</td>\n",
       "      <td>0.120099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EVFM</th>\n",
       "      <td>0.028523</td>\n",
       "      <td>0.040025</td>\n",
       "      <td>0.016409</td>\n",
       "      <td>-0.010143</td>\n",
       "      <td>0.046357</td>\n",
       "      <td>0.011167</td>\n",
       "      <td>0.014526</td>\n",
       "      <td>0.022240</td>\n",
       "      <td>-0.050261</td>\n",
       "      <td>0.031639</td>\n",
       "      <td>...</td>\n",
       "      <td>0.041026</td>\n",
       "      <td>-0.001547</td>\n",
       "      <td>0.028728</td>\n",
       "      <td>-0.015333</td>\n",
       "      <td>0.008108</td>\n",
       "      <td>-0.029947</td>\n",
       "      <td>0.006777</td>\n",
       "      <td>0.023966</td>\n",
       "      <td>0.019171</td>\n",
       "      <td>0.046903</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TGTX</th>\n",
       "      <td>0.041271</td>\n",
       "      <td>0.159973</td>\n",
       "      <td>0.227878</td>\n",
       "      <td>0.069397</td>\n",
       "      <td>0.124395</td>\n",
       "      <td>0.160637</td>\n",
       "      <td>0.179684</td>\n",
       "      <td>0.061717</td>\n",
       "      <td>0.093416</td>\n",
       "      <td>0.073416</td>\n",
       "      <td>...</td>\n",
       "      <td>0.190317</td>\n",
       "      <td>0.240509</td>\n",
       "      <td>0.245353</td>\n",
       "      <td>0.153695</td>\n",
       "      <td>0.096685</td>\n",
       "      <td>0.125536</td>\n",
       "      <td>0.192032</td>\n",
       "      <td>0.069359</td>\n",
       "      <td>0.109745</td>\n",
       "      <td>0.244285</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ATU</th>\n",
       "      <td>0.128803</td>\n",
       "      <td>0.175366</td>\n",
       "      <td>0.470649</td>\n",
       "      <td>0.234532</td>\n",
       "      <td>0.271948</td>\n",
       "      <td>0.219546</td>\n",
       "      <td>0.347223</td>\n",
       "      <td>0.052403</td>\n",
       "      <td>0.128425</td>\n",
       "      <td>0.275074</td>\n",
       "      <td>...</td>\n",
       "      <td>0.380430</td>\n",
       "      <td>0.449769</td>\n",
       "      <td>0.447563</td>\n",
       "      <td>0.199417</td>\n",
       "      <td>0.166804</td>\n",
       "      <td>0.218071</td>\n",
       "      <td>0.479971</td>\n",
       "      <td>0.168863</td>\n",
       "      <td>0.124439</td>\n",
       "      <td>0.148138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BTX</th>\n",
       "      <td>0.015919</td>\n",
       "      <td>0.101307</td>\n",
       "      <td>0.262886</td>\n",
       "      <td>0.107030</td>\n",
       "      <td>0.181545</td>\n",
       "      <td>0.187229</td>\n",
       "      <td>0.218360</td>\n",
       "      <td>0.024691</td>\n",
       "      <td>0.102722</td>\n",
       "      <td>0.087657</td>\n",
       "      <td>...</td>\n",
       "      <td>0.210808</td>\n",
       "      <td>0.258619</td>\n",
       "      <td>0.220801</td>\n",
       "      <td>0.152602</td>\n",
       "      <td>0.161866</td>\n",
       "      <td>0.209665</td>\n",
       "      <td>0.256747</td>\n",
       "      <td>0.130042</td>\n",
       "      <td>0.085556</td>\n",
       "      <td>0.221017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CYTK</th>\n",
       "      <td>0.091739</td>\n",
       "      <td>0.071528</td>\n",
       "      <td>0.187586</td>\n",
       "      <td>0.082830</td>\n",
       "      <td>0.127924</td>\n",
       "      <td>0.172689</td>\n",
       "      <td>0.150098</td>\n",
       "      <td>0.090342</td>\n",
       "      <td>0.022486</td>\n",
       "      <td>0.076011</td>\n",
       "      <td>...</td>\n",
       "      <td>0.159389</td>\n",
       "      <td>0.150879</td>\n",
       "      <td>0.217903</td>\n",
       "      <td>0.098130</td>\n",
       "      <td>0.110309</td>\n",
       "      <td>0.142934</td>\n",
       "      <td>0.227568</td>\n",
       "      <td>0.065549</td>\n",
       "      <td>0.083965</td>\n",
       "      <td>0.223017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TUSA</th>\n",
       "      <td>0.159539</td>\n",
       "      <td>0.198175</td>\n",
       "      <td>0.548806</td>\n",
       "      <td>0.228190</td>\n",
       "      <td>0.341959</td>\n",
       "      <td>0.234206</td>\n",
       "      <td>0.383696</td>\n",
       "      <td>0.049045</td>\n",
       "      <td>0.201214</td>\n",
       "      <td>0.216596</td>\n",
       "      <td>...</td>\n",
       "      <td>0.460575</td>\n",
       "      <td>0.493666</td>\n",
       "      <td>0.581971</td>\n",
       "      <td>0.225026</td>\n",
       "      <td>0.173053</td>\n",
       "      <td>0.274057</td>\n",
       "      <td>0.451863</td>\n",
       "      <td>0.181451</td>\n",
       "      <td>0.118798</td>\n",
       "      <td>0.227751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HEWG</th>\n",
       "      <td>0.155926</td>\n",
       "      <td>0.183518</td>\n",
       "      <td>0.667209</td>\n",
       "      <td>0.214085</td>\n",
       "      <td>0.505562</td>\n",
       "      <td>0.260809</td>\n",
       "      <td>0.406639</td>\n",
       "      <td>0.069997</td>\n",
       "      <td>0.185096</td>\n",
       "      <td>0.204733</td>\n",
       "      <td>...</td>\n",
       "      <td>0.369113</td>\n",
       "      <td>0.614084</td>\n",
       "      <td>0.628977</td>\n",
       "      <td>0.241490</td>\n",
       "      <td>0.221676</td>\n",
       "      <td>0.318885</td>\n",
       "      <td>0.481660</td>\n",
       "      <td>0.157864</td>\n",
       "      <td>0.106048</td>\n",
       "      <td>0.191722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FRPH</th>\n",
       "      <td>0.090629</td>\n",
       "      <td>0.165406</td>\n",
       "      <td>0.231693</td>\n",
       "      <td>0.137591</td>\n",
       "      <td>0.131616</td>\n",
       "      <td>0.221453</td>\n",
       "      <td>0.216296</td>\n",
       "      <td>0.009651</td>\n",
       "      <td>0.095344</td>\n",
       "      <td>0.088447</td>\n",
       "      <td>...</td>\n",
       "      <td>0.171903</td>\n",
       "      <td>0.232114</td>\n",
       "      <td>0.240377</td>\n",
       "      <td>0.129369</td>\n",
       "      <td>0.164924</td>\n",
       "      <td>0.277878</td>\n",
       "      <td>0.302945</td>\n",
       "      <td>0.118678</td>\n",
       "      <td>0.096547</td>\n",
       "      <td>0.091925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ATNM</th>\n",
       "      <td>0.081901</td>\n",
       "      <td>0.105717</td>\n",
       "      <td>0.201347</td>\n",
       "      <td>0.083898</td>\n",
       "      <td>0.085076</td>\n",
       "      <td>0.143144</td>\n",
       "      <td>0.109940</td>\n",
       "      <td>0.013036</td>\n",
       "      <td>0.080126</td>\n",
       "      <td>0.135597</td>\n",
       "      <td>...</td>\n",
       "      <td>0.194225</td>\n",
       "      <td>0.146410</td>\n",
       "      <td>0.181535</td>\n",
       "      <td>0.118061</td>\n",
       "      <td>0.132194</td>\n",
       "      <td>0.049542</td>\n",
       "      <td>0.129684</td>\n",
       "      <td>0.041530</td>\n",
       "      <td>0.058843</td>\n",
       "      <td>0.047156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UBFO</th>\n",
       "      <td>0.050129</td>\n",
       "      <td>0.008996</td>\n",
       "      <td>0.143665</td>\n",
       "      <td>0.012996</td>\n",
       "      <td>0.018630</td>\n",
       "      <td>0.033522</td>\n",
       "      <td>0.071987</td>\n",
       "      <td>0.071241</td>\n",
       "      <td>0.018215</td>\n",
       "      <td>0.052691</td>\n",
       "      <td>...</td>\n",
       "      <td>0.043020</td>\n",
       "      <td>0.096270</td>\n",
       "      <td>0.101742</td>\n",
       "      <td>0.062323</td>\n",
       "      <td>0.032127</td>\n",
       "      <td>0.131986</td>\n",
       "      <td>0.113483</td>\n",
       "      <td>0.094348</td>\n",
       "      <td>0.093482</td>\n",
       "      <td>0.035911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FIVN</th>\n",
       "      <td>-0.071988</td>\n",
       "      <td>0.157519</td>\n",
       "      <td>0.220491</td>\n",
       "      <td>0.083745</td>\n",
       "      <td>0.131045</td>\n",
       "      <td>0.248860</td>\n",
       "      <td>0.270405</td>\n",
       "      <td>-0.032710</td>\n",
       "      <td>0.025050</td>\n",
       "      <td>0.115624</td>\n",
       "      <td>...</td>\n",
       "      <td>0.150397</td>\n",
       "      <td>0.252765</td>\n",
       "      <td>0.307605</td>\n",
       "      <td>0.139544</td>\n",
       "      <td>0.079487</td>\n",
       "      <td>0.140948</td>\n",
       "      <td>0.245787</td>\n",
       "      <td>0.084515</td>\n",
       "      <td>0.084328</td>\n",
       "      <td>0.148796</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PEG</th>\n",
       "      <td>0.128308</td>\n",
       "      <td>0.035691</td>\n",
       "      <td>0.049391</td>\n",
       "      <td>0.204540</td>\n",
       "      <td>0.196740</td>\n",
       "      <td>0.076594</td>\n",
       "      <td>0.080335</td>\n",
       "      <td>0.067961</td>\n",
       "      <td>-0.020563</td>\n",
       "      <td>0.062474</td>\n",
       "      <td>...</td>\n",
       "      <td>0.124701</td>\n",
       "      <td>0.246099</td>\n",
       "      <td>0.240720</td>\n",
       "      <td>0.197653</td>\n",
       "      <td>0.036505</td>\n",
       "      <td>0.041385</td>\n",
       "      <td>0.079816</td>\n",
       "      <td>0.093074</td>\n",
       "      <td>0.011771</td>\n",
       "      <td>-0.003474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KLAC</th>\n",
       "      <td>0.075333</td>\n",
       "      <td>0.158815</td>\n",
       "      <td>0.352815</td>\n",
       "      <td>0.182717</td>\n",
       "      <td>0.204692</td>\n",
       "      <td>0.211730</td>\n",
       "      <td>0.345780</td>\n",
       "      <td>0.048992</td>\n",
       "      <td>0.059905</td>\n",
       "      <td>0.135723</td>\n",
       "      <td>...</td>\n",
       "      <td>0.214645</td>\n",
       "      <td>0.406202</td>\n",
       "      <td>0.434366</td>\n",
       "      <td>0.120923</td>\n",
       "      <td>0.124602</td>\n",
       "      <td>0.184808</td>\n",
       "      <td>0.350513</td>\n",
       "      <td>0.098451</td>\n",
       "      <td>0.017188</td>\n",
       "      <td>0.205949</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UNT</th>\n",
       "      <td>0.062327</td>\n",
       "      <td>0.131831</td>\n",
       "      <td>0.364832</td>\n",
       "      <td>0.123948</td>\n",
       "      <td>0.190033</td>\n",
       "      <td>0.128401</td>\n",
       "      <td>0.201714</td>\n",
       "      <td>0.066843</td>\n",
       "      <td>0.174611</td>\n",
       "      <td>0.407000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.588566</td>\n",
       "      <td>0.406587</td>\n",
       "      <td>0.323144</td>\n",
       "      <td>0.259230</td>\n",
       "      <td>0.193528</td>\n",
       "      <td>0.154522</td>\n",
       "      <td>0.299601</td>\n",
       "      <td>0.165169</td>\n",
       "      <td>0.116499</td>\n",
       "      <td>0.121088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WATT</th>\n",
       "      <td>0.075617</td>\n",
       "      <td>0.024516</td>\n",
       "      <td>0.159659</td>\n",
       "      <td>0.063039</td>\n",
       "      <td>0.101938</td>\n",
       "      <td>0.059304</td>\n",
       "      <td>0.129068</td>\n",
       "      <td>0.038084</td>\n",
       "      <td>0.030054</td>\n",
       "      <td>0.088911</td>\n",
       "      <td>...</td>\n",
       "      <td>0.167496</td>\n",
       "      <td>0.163125</td>\n",
       "      <td>0.163022</td>\n",
       "      <td>0.058825</td>\n",
       "      <td>0.108571</td>\n",
       "      <td>0.109206</td>\n",
       "      <td>0.144329</td>\n",
       "      <td>0.089944</td>\n",
       "      <td>0.045934</td>\n",
       "      <td>0.120415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AVGR</th>\n",
       "      <td>-0.041364</td>\n",
       "      <td>0.062540</td>\n",
       "      <td>0.068666</td>\n",
       "      <td>0.014282</td>\n",
       "      <td>0.043581</td>\n",
       "      <td>0.079799</td>\n",
       "      <td>0.066799</td>\n",
       "      <td>-0.000607</td>\n",
       "      <td>0.047128</td>\n",
       "      <td>0.023644</td>\n",
       "      <td>...</td>\n",
       "      <td>0.043290</td>\n",
       "      <td>0.025630</td>\n",
       "      <td>0.088029</td>\n",
       "      <td>0.002737</td>\n",
       "      <td>0.007887</td>\n",
       "      <td>0.119533</td>\n",
       "      <td>0.068010</td>\n",
       "      <td>0.009188</td>\n",
       "      <td>0.039583</td>\n",
       "      <td>0.071067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DEF</th>\n",
       "      <td>0.197265</td>\n",
       "      <td>0.216145</td>\n",
       "      <td>0.549774</td>\n",
       "      <td>0.330668</td>\n",
       "      <td>0.422593</td>\n",
       "      <td>0.310270</td>\n",
       "      <td>0.452375</td>\n",
       "      <td>0.090888</td>\n",
       "      <td>0.166888</td>\n",
       "      <td>0.241814</td>\n",
       "      <td>...</td>\n",
       "      <td>0.447933</td>\n",
       "      <td>0.632359</td>\n",
       "      <td>0.668545</td>\n",
       "      <td>0.269358</td>\n",
       "      <td>0.191405</td>\n",
       "      <td>0.284225</td>\n",
       "      <td>0.503433</td>\n",
       "      <td>0.210915</td>\n",
       "      <td>0.084051</td>\n",
       "      <td>0.185421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VIPS</th>\n",
       "      <td>0.043739</td>\n",
       "      <td>0.071959</td>\n",
       "      <td>0.269128</td>\n",
       "      <td>0.140901</td>\n",
       "      <td>0.214086</td>\n",
       "      <td>0.129370</td>\n",
       "      <td>0.185265</td>\n",
       "      <td>0.118901</td>\n",
       "      <td>0.076925</td>\n",
       "      <td>0.112553</td>\n",
       "      <td>...</td>\n",
       "      <td>0.206245</td>\n",
       "      <td>0.335226</td>\n",
       "      <td>0.314515</td>\n",
       "      <td>0.095120</td>\n",
       "      <td>0.110733</td>\n",
       "      <td>0.078509</td>\n",
       "      <td>0.241571</td>\n",
       "      <td>0.097961</td>\n",
       "      <td>0.047289</td>\n",
       "      <td>0.170534</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CEI</th>\n",
       "      <td>0.023965</td>\n",
       "      <td>0.077584</td>\n",
       "      <td>0.020841</td>\n",
       "      <td>0.042549</td>\n",
       "      <td>0.032376</td>\n",
       "      <td>-0.007909</td>\n",
       "      <td>0.037637</td>\n",
       "      <td>-0.039738</td>\n",
       "      <td>0.051251</td>\n",
       "      <td>0.171021</td>\n",
       "      <td>...</td>\n",
       "      <td>0.158683</td>\n",
       "      <td>0.054979</td>\n",
       "      <td>0.048295</td>\n",
       "      <td>0.063058</td>\n",
       "      <td>0.026491</td>\n",
       "      <td>0.010128</td>\n",
       "      <td>0.055442</td>\n",
       "      <td>0.012619</td>\n",
       "      <td>0.032325</td>\n",
       "      <td>0.027552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FXA</th>\n",
       "      <td>0.037052</td>\n",
       "      <td>0.087767</td>\n",
       "      <td>0.246213</td>\n",
       "      <td>0.188201</td>\n",
       "      <td>0.292077</td>\n",
       "      <td>0.081573</td>\n",
       "      <td>0.189557</td>\n",
       "      <td>0.049475</td>\n",
       "      <td>0.125636</td>\n",
       "      <td>0.211368</td>\n",
       "      <td>...</td>\n",
       "      <td>0.296863</td>\n",
       "      <td>0.571735</td>\n",
       "      <td>0.314166</td>\n",
       "      <td>0.156116</td>\n",
       "      <td>0.160129</td>\n",
       "      <td>0.106929</td>\n",
       "      <td>0.211595</td>\n",
       "      <td>0.220596</td>\n",
       "      <td>-0.006677</td>\n",
       "      <td>0.091933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UTHR</th>\n",
       "      <td>0.148944</td>\n",
       "      <td>0.188859</td>\n",
       "      <td>0.325118</td>\n",
       "      <td>0.132613</td>\n",
       "      <td>0.134492</td>\n",
       "      <td>0.194932</td>\n",
       "      <td>0.198037</td>\n",
       "      <td>-0.002817</td>\n",
       "      <td>0.091714</td>\n",
       "      <td>0.063821</td>\n",
       "      <td>...</td>\n",
       "      <td>0.198677</td>\n",
       "      <td>0.260207</td>\n",
       "      <td>0.290054</td>\n",
       "      <td>0.147013</td>\n",
       "      <td>0.108058</td>\n",
       "      <td>0.140727</td>\n",
       "      <td>0.287345</td>\n",
       "      <td>0.074093</td>\n",
       "      <td>0.101162</td>\n",
       "      <td>0.216258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIK</th>\n",
       "      <td>0.127129</td>\n",
       "      <td>0.152371</td>\n",
       "      <td>0.328228</td>\n",
       "      <td>0.185183</td>\n",
       "      <td>0.213639</td>\n",
       "      <td>0.113609</td>\n",
       "      <td>0.174941</td>\n",
       "      <td>0.050916</td>\n",
       "      <td>0.087998</td>\n",
       "      <td>0.137953</td>\n",
       "      <td>...</td>\n",
       "      <td>0.266907</td>\n",
       "      <td>0.292900</td>\n",
       "      <td>0.311491</td>\n",
       "      <td>0.192239</td>\n",
       "      <td>0.142697</td>\n",
       "      <td>0.097453</td>\n",
       "      <td>0.280671</td>\n",
       "      <td>0.098367</td>\n",
       "      <td>0.071400</td>\n",
       "      <td>0.178621</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EXK</th>\n",
       "      <td>0.026583</td>\n",
       "      <td>0.024567</td>\n",
       "      <td>-0.021318</td>\n",
       "      <td>0.055342</td>\n",
       "      <td>0.087633</td>\n",
       "      <td>0.013044</td>\n",
       "      <td>0.066645</td>\n",
       "      <td>0.061561</td>\n",
       "      <td>0.029851</td>\n",
       "      <td>0.170491</td>\n",
       "      <td>...</td>\n",
       "      <td>0.194818</td>\n",
       "      <td>0.268437</td>\n",
       "      <td>0.046252</td>\n",
       "      <td>0.115376</td>\n",
       "      <td>0.095853</td>\n",
       "      <td>0.065496</td>\n",
       "      <td>0.023086</td>\n",
       "      <td>0.134894</td>\n",
       "      <td>0.047765</td>\n",
       "      <td>0.027007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CMA</th>\n",
       "      <td>0.111772</td>\n",
       "      <td>0.186074</td>\n",
       "      <td>0.762735</td>\n",
       "      <td>0.152897</td>\n",
       "      <td>0.337103</td>\n",
       "      <td>0.240371</td>\n",
       "      <td>0.332716</td>\n",
       "      <td>0.044038</td>\n",
       "      <td>0.181688</td>\n",
       "      <td>0.198468</td>\n",
       "      <td>...</td>\n",
       "      <td>0.392829</td>\n",
       "      <td>0.466158</td>\n",
       "      <td>0.491216</td>\n",
       "      <td>0.205492</td>\n",
       "      <td>0.170726</td>\n",
       "      <td>0.334183</td>\n",
       "      <td>0.464065</td>\n",
       "      <td>0.152544</td>\n",
       "      <td>0.159793</td>\n",
       "      <td>0.153563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SNOA</th>\n",
       "      <td>0.040593</td>\n",
       "      <td>0.066074</td>\n",
       "      <td>0.105551</td>\n",
       "      <td>0.045261</td>\n",
       "      <td>0.056888</td>\n",
       "      <td>0.007577</td>\n",
       "      <td>0.043958</td>\n",
       "      <td>-0.000001</td>\n",
       "      <td>0.077501</td>\n",
       "      <td>0.083089</td>\n",
       "      <td>...</td>\n",
       "      <td>0.143166</td>\n",
       "      <td>0.086576</td>\n",
       "      <td>0.137016</td>\n",
       "      <td>0.086707</td>\n",
       "      <td>0.010204</td>\n",
       "      <td>0.065073</td>\n",
       "      <td>0.061300</td>\n",
       "      <td>0.066829</td>\n",
       "      <td>0.028434</td>\n",
       "      <td>0.019553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BOTJ</th>\n",
       "      <td>0.008511</td>\n",
       "      <td>-0.019073</td>\n",
       "      <td>0.034630</td>\n",
       "      <td>0.002120</td>\n",
       "      <td>0.029758</td>\n",
       "      <td>-0.019327</td>\n",
       "      <td>-0.015527</td>\n",
       "      <td>0.028354</td>\n",
       "      <td>0.022388</td>\n",
       "      <td>-0.036160</td>\n",
       "      <td>...</td>\n",
       "      <td>0.057431</td>\n",
       "      <td>0.031457</td>\n",
       "      <td>0.086401</td>\n",
       "      <td>0.037364</td>\n",
       "      <td>-0.018689</td>\n",
       "      <td>0.029828</td>\n",
       "      <td>0.020327</td>\n",
       "      <td>-0.010179</td>\n",
       "      <td>0.047151</td>\n",
       "      <td>-0.002841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AIR</th>\n",
       "      <td>0.144945</td>\n",
       "      <td>0.185905</td>\n",
       "      <td>0.370357</td>\n",
       "      <td>0.186326</td>\n",
       "      <td>0.197357</td>\n",
       "      <td>0.200502</td>\n",
       "      <td>0.319465</td>\n",
       "      <td>0.037308</td>\n",
       "      <td>0.176902</td>\n",
       "      <td>0.226487</td>\n",
       "      <td>...</td>\n",
       "      <td>0.278841</td>\n",
       "      <td>0.362387</td>\n",
       "      <td>0.393758</td>\n",
       "      <td>0.195208</td>\n",
       "      <td>0.138018</td>\n",
       "      <td>0.271175</td>\n",
       "      <td>0.426088</td>\n",
       "      <td>0.170690</td>\n",
       "      <td>0.097361</td>\n",
       "      <td>0.161841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GER</th>\n",
       "      <td>0.110893</td>\n",
       "      <td>0.160279</td>\n",
       "      <td>0.423860</td>\n",
       "      <td>0.149429</td>\n",
       "      <td>0.301992</td>\n",
       "      <td>0.138302</td>\n",
       "      <td>0.233829</td>\n",
       "      <td>0.149547</td>\n",
       "      <td>0.209557</td>\n",
       "      <td>0.384791</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.467148</td>\n",
       "      <td>0.446534</td>\n",
       "      <td>0.310832</td>\n",
       "      <td>0.183449</td>\n",
       "      <td>0.175788</td>\n",
       "      <td>0.339478</td>\n",
       "      <td>0.168689</td>\n",
       "      <td>0.091420</td>\n",
       "      <td>0.141021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DVYE</th>\n",
       "      <td>0.095780</td>\n",
       "      <td>0.177127</td>\n",
       "      <td>0.539164</td>\n",
       "      <td>0.247542</td>\n",
       "      <td>0.460423</td>\n",
       "      <td>0.204934</td>\n",
       "      <td>0.363862</td>\n",
       "      <td>0.080735</td>\n",
       "      <td>0.163020</td>\n",
       "      <td>0.304740</td>\n",
       "      <td>...</td>\n",
       "      <td>0.467148</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.592029</td>\n",
       "      <td>0.303620</td>\n",
       "      <td>0.208867</td>\n",
       "      <td>0.239941</td>\n",
       "      <td>0.405154</td>\n",
       "      <td>0.373606</td>\n",
       "      <td>0.099811</td>\n",
       "      <td>0.182622</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GAM</th>\n",
       "      <td>0.162096</td>\n",
       "      <td>0.184769</td>\n",
       "      <td>0.594398</td>\n",
       "      <td>0.236449</td>\n",
       "      <td>0.400955</td>\n",
       "      <td>0.239660</td>\n",
       "      <td>0.396882</td>\n",
       "      <td>0.053558</td>\n",
       "      <td>0.120953</td>\n",
       "      <td>0.212286</td>\n",
       "      <td>...</td>\n",
       "      <td>0.446534</td>\n",
       "      <td>0.592029</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.283000</td>\n",
       "      <td>0.144721</td>\n",
       "      <td>0.253973</td>\n",
       "      <td>0.446146</td>\n",
       "      <td>0.190536</td>\n",
       "      <td>0.127072</td>\n",
       "      <td>0.197384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AY</th>\n",
       "      <td>0.059253</td>\n",
       "      <td>0.115473</td>\n",
       "      <td>0.246211</td>\n",
       "      <td>0.136715</td>\n",
       "      <td>0.183211</td>\n",
       "      <td>0.145081</td>\n",
       "      <td>0.168621</td>\n",
       "      <td>0.063280</td>\n",
       "      <td>0.139755</td>\n",
       "      <td>0.132744</td>\n",
       "      <td>...</td>\n",
       "      <td>0.310832</td>\n",
       "      <td>0.303620</td>\n",
       "      <td>0.283000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.153110</td>\n",
       "      <td>0.137223</td>\n",
       "      <td>0.155926</td>\n",
       "      <td>0.105611</td>\n",
       "      <td>0.105512</td>\n",
       "      <td>0.109073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LAC</th>\n",
       "      <td>0.013526</td>\n",
       "      <td>0.056405</td>\n",
       "      <td>0.189167</td>\n",
       "      <td>0.032140</td>\n",
       "      <td>0.101225</td>\n",
       "      <td>0.097276</td>\n",
       "      <td>0.126861</td>\n",
       "      <td>0.077096</td>\n",
       "      <td>0.110883</td>\n",
       "      <td>0.101404</td>\n",
       "      <td>...</td>\n",
       "      <td>0.183449</td>\n",
       "      <td>0.208867</td>\n",
       "      <td>0.144721</td>\n",
       "      <td>0.153110</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.102443</td>\n",
       "      <td>0.110697</td>\n",
       "      <td>0.051578</td>\n",
       "      <td>0.060029</td>\n",
       "      <td>0.073254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NKSH</th>\n",
       "      <td>0.123530</td>\n",
       "      <td>0.167408</td>\n",
       "      <td>0.330709</td>\n",
       "      <td>0.132911</td>\n",
       "      <td>0.148344</td>\n",
       "      <td>0.217666</td>\n",
       "      <td>0.230386</td>\n",
       "      <td>0.073506</td>\n",
       "      <td>0.091549</td>\n",
       "      <td>0.118872</td>\n",
       "      <td>...</td>\n",
       "      <td>0.175788</td>\n",
       "      <td>0.239941</td>\n",
       "      <td>0.253973</td>\n",
       "      <td>0.137223</td>\n",
       "      <td>0.102443</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.302054</td>\n",
       "      <td>0.125397</td>\n",
       "      <td>0.094005</td>\n",
       "      <td>0.108091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EME</th>\n",
       "      <td>0.116517</td>\n",
       "      <td>0.230055</td>\n",
       "      <td>0.481906</td>\n",
       "      <td>0.249026</td>\n",
       "      <td>0.255465</td>\n",
       "      <td>0.243584</td>\n",
       "      <td>0.403664</td>\n",
       "      <td>0.056087</td>\n",
       "      <td>0.152449</td>\n",
       "      <td>0.201675</td>\n",
       "      <td>...</td>\n",
       "      <td>0.339478</td>\n",
       "      <td>0.405154</td>\n",
       "      <td>0.446146</td>\n",
       "      <td>0.155926</td>\n",
       "      <td>0.110697</td>\n",
       "      <td>0.302054</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.159480</td>\n",
       "      <td>0.089861</td>\n",
       "      <td>0.144744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BBDO</th>\n",
       "      <td>0.069471</td>\n",
       "      <td>0.113140</td>\n",
       "      <td>0.182026</td>\n",
       "      <td>0.132804</td>\n",
       "      <td>0.144951</td>\n",
       "      <td>0.068564</td>\n",
       "      <td>0.162042</td>\n",
       "      <td>-0.019714</td>\n",
       "      <td>0.057738</td>\n",
       "      <td>0.148910</td>\n",
       "      <td>...</td>\n",
       "      <td>0.168689</td>\n",
       "      <td>0.373606</td>\n",
       "      <td>0.190536</td>\n",
       "      <td>0.105611</td>\n",
       "      <td>0.051578</td>\n",
       "      <td>0.125397</td>\n",
       "      <td>0.159480</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.037893</td>\n",
       "      <td>0.049618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GRIF</th>\n",
       "      <td>0.022214</td>\n",
       "      <td>0.154118</td>\n",
       "      <td>0.143624</td>\n",
       "      <td>0.060087</td>\n",
       "      <td>0.048907</td>\n",
       "      <td>0.076308</td>\n",
       "      <td>0.073413</td>\n",
       "      <td>0.083590</td>\n",
       "      <td>0.020015</td>\n",
       "      <td>-0.009387</td>\n",
       "      <td>...</td>\n",
       "      <td>0.091420</td>\n",
       "      <td>0.099811</td>\n",
       "      <td>0.127072</td>\n",
       "      <td>0.105512</td>\n",
       "      <td>0.060029</td>\n",
       "      <td>0.094005</td>\n",
       "      <td>0.089861</td>\n",
       "      <td>0.037893</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.022069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IMGN</th>\n",
       "      <td>0.045443</td>\n",
       "      <td>0.028745</td>\n",
       "      <td>0.223703</td>\n",
       "      <td>0.037325</td>\n",
       "      <td>0.155452</td>\n",
       "      <td>0.089468</td>\n",
       "      <td>0.161721</td>\n",
       "      <td>0.042534</td>\n",
       "      <td>0.066018</td>\n",
       "      <td>0.080556</td>\n",
       "      <td>...</td>\n",
       "      <td>0.141021</td>\n",
       "      <td>0.182622</td>\n",
       "      <td>0.197384</td>\n",
       "      <td>0.109073</td>\n",
       "      <td>0.073254</td>\n",
       "      <td>0.108091</td>\n",
       "      <td>0.144744</td>\n",
       "      <td>0.049618</td>\n",
       "      <td>0.022069</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>50 rows × 50 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            DF      SQBG         C       PPC       VOD      TRUP      NATI  \\\n",
       "DF    1.000000  0.134295  0.117884  0.185416  0.134690  0.072274  0.079081   \n",
       "SQBG  0.134295  1.000000  0.188575  0.073260  0.085516  0.144972  0.159547   \n",
       "C     0.117884  0.188575  1.000000  0.195809  0.401970  0.250866  0.358793   \n",
       "PPC   0.185416  0.073260  0.195809  1.000000  0.217682  0.100858  0.160136   \n",
       "VOD   0.134690  0.085516  0.401970  0.217682  1.000000  0.054646  0.224806   \n",
       "TRUP  0.072274  0.144972  0.250866  0.100858  0.054646  1.000000  0.213302   \n",
       "NATI  0.079081  0.159547  0.358793  0.160136  0.224806  0.213302  1.000000   \n",
       "GNUS  0.059838  0.086579  0.089070  0.047757  0.109669 -0.004193  0.025573   \n",
       "RINF  0.030613  0.105411  0.207429  0.096466  0.091964  0.068103  0.075845   \n",
       "DMLP  0.082329  0.130219  0.189276  0.102827  0.123914  0.087518  0.141107   \n",
       "NTES  0.007202  0.038813  0.239071  0.082621  0.242499  0.100268  0.207969   \n",
       "EMD   0.063258  0.111098  0.267974  0.165229  0.261423  0.091863  0.146243   \n",
       "QMN   0.093452  0.105410  0.149722  0.094157  0.179511  0.140612  0.188852   \n",
       "EVFM  0.028523  0.040025  0.016409 -0.010143  0.046357  0.011167  0.014526   \n",
       "TGTX  0.041271  0.159973  0.227878  0.069397  0.124395  0.160637  0.179684   \n",
       "ATU   0.128803  0.175366  0.470649  0.234532  0.271948  0.219546  0.347223   \n",
       "BTX   0.015919  0.101307  0.262886  0.107030  0.181545  0.187229  0.218360   \n",
       "CYTK  0.091739  0.071528  0.187586  0.082830  0.127924  0.172689  0.150098   \n",
       "TUSA  0.159539  0.198175  0.548806  0.228190  0.341959  0.234206  0.383696   \n",
       "HEWG  0.155926  0.183518  0.667209  0.214085  0.505562  0.260809  0.406639   \n",
       "FRPH  0.090629  0.165406  0.231693  0.137591  0.131616  0.221453  0.216296   \n",
       "ATNM  0.081901  0.105717  0.201347  0.083898  0.085076  0.143144  0.109940   \n",
       "UBFO  0.050129  0.008996  0.143665  0.012996  0.018630  0.033522  0.071987   \n",
       "FIVN -0.071988  0.157519  0.220491  0.083745  0.131045  0.248860  0.270405   \n",
       "PEG   0.128308  0.035691  0.049391  0.204540  0.196740  0.076594  0.080335   \n",
       "KLAC  0.075333  0.158815  0.352815  0.182717  0.204692  0.211730  0.345780   \n",
       "UNT   0.062327  0.131831  0.364832  0.123948  0.190033  0.128401  0.201714   \n",
       "WATT  0.075617  0.024516  0.159659  0.063039  0.101938  0.059304  0.129068   \n",
       "AVGR -0.041364  0.062540  0.068666  0.014282  0.043581  0.079799  0.066799   \n",
       "DEF   0.197265  0.216145  0.549774  0.330668  0.422593  0.310270  0.452375   \n",
       "VIPS  0.043739  0.071959  0.269128  0.140901  0.214086  0.129370  0.185265   \n",
       "CEI   0.023965  0.077584  0.020841  0.042549  0.032376 -0.007909  0.037637   \n",
       "FXA   0.037052  0.087767  0.246213  0.188201  0.292077  0.081573  0.189557   \n",
       "UTHR  0.148944  0.188859  0.325118  0.132613  0.134492  0.194932  0.198037   \n",
       "MIK   0.127129  0.152371  0.328228  0.185183  0.213639  0.113609  0.174941   \n",
       "EXK   0.026583  0.024567 -0.021318  0.055342  0.087633  0.013044  0.066645   \n",
       "CMA   0.111772  0.186074  0.762735  0.152897  0.337103  0.240371  0.332716   \n",
       "SNOA  0.040593  0.066074  0.105551  0.045261  0.056888  0.007577  0.043958   \n",
       "BOTJ  0.008511 -0.019073  0.034630  0.002120  0.029758 -0.019327 -0.015527   \n",
       "AIR   0.144945  0.185905  0.370357  0.186326  0.197357  0.200502  0.319465   \n",
       "GER   0.110893  0.160279  0.423860  0.149429  0.301992  0.138302  0.233829   \n",
       "DVYE  0.095780  0.177127  0.539164  0.247542  0.460423  0.204934  0.363862   \n",
       "GAM   0.162096  0.184769  0.594398  0.236449  0.400955  0.239660  0.396882   \n",
       "AY    0.059253  0.115473  0.246211  0.136715  0.183211  0.145081  0.168621   \n",
       "LAC   0.013526  0.056405  0.189167  0.032140  0.101225  0.097276  0.126861   \n",
       "NKSH  0.123530  0.167408  0.330709  0.132911  0.148344  0.217666  0.230386   \n",
       "EME   0.116517  0.230055  0.481906  0.249026  0.255465  0.243584  0.403664   \n",
       "BBDO  0.069471  0.113140  0.182026  0.132804  0.144951  0.068564  0.162042   \n",
       "GRIF  0.022214  0.154118  0.143624  0.060087  0.048907  0.076308  0.073413   \n",
       "IMGN  0.045443  0.028745  0.223703  0.037325  0.155452  0.089468  0.161721   \n",
       "\n",
       "          GNUS      RINF      DMLP  ...       GER      DVYE       GAM  \\\n",
       "DF    0.059838  0.030613  0.082329  ...  0.110893  0.095780  0.162096   \n",
       "SQBG  0.086579  0.105411  0.130219  ...  0.160279  0.177127  0.184769   \n",
       "C     0.089070  0.207429  0.189276  ...  0.423860  0.539164  0.594398   \n",
       "PPC   0.047757  0.096466  0.102827  ...  0.149429  0.247542  0.236449   \n",
       "VOD   0.109669  0.091964  0.123914  ...  0.301992  0.460423  0.400955   \n",
       "TRUP -0.004193  0.068103  0.087518  ...  0.138302  0.204934  0.239660   \n",
       "NATI  0.025573  0.075845  0.141107  ...  0.233829  0.363862  0.396882   \n",
       "GNUS  1.000000  0.033590  0.047493  ...  0.149547  0.080735  0.053558   \n",
       "RINF  0.033590  1.000000  0.115095  ...  0.209557  0.163020  0.120953   \n",
       "DMLP  0.047493  0.115095  1.000000  ...  0.384791  0.304740  0.212286   \n",
       "NTES  0.061409  0.055390  0.060003  ...  0.172861  0.399044  0.278208   \n",
       "EMD   0.058068  0.118041  0.203802  ...  0.405795  0.447581  0.398401   \n",
       "QMN   0.101747  0.089899  0.149836  ...  0.232329  0.258209  0.299926   \n",
       "EVFM  0.022240 -0.050261  0.031639  ...  0.041026 -0.001547  0.028728   \n",
       "TGTX  0.061717  0.093416  0.073416  ...  0.190317  0.240509  0.245353   \n",
       "ATU   0.052403  0.128425  0.275074  ...  0.380430  0.449769  0.447563   \n",
       "BTX   0.024691  0.102722  0.087657  ...  0.210808  0.258619  0.220801   \n",
       "CYTK  0.090342  0.022486  0.076011  ...  0.159389  0.150879  0.217903   \n",
       "TUSA  0.049045  0.201214  0.216596  ...  0.460575  0.493666  0.581971   \n",
       "HEWG  0.069997  0.185096  0.204733  ...  0.369113  0.614084  0.628977   \n",
       "FRPH  0.009651  0.095344  0.088447  ...  0.171903  0.232114  0.240377   \n",
       "ATNM  0.013036  0.080126  0.135597  ...  0.194225  0.146410  0.181535   \n",
       "UBFO  0.071241  0.018215  0.052691  ...  0.043020  0.096270  0.101742   \n",
       "FIVN -0.032710  0.025050  0.115624  ...  0.150397  0.252765  0.307605   \n",
       "PEG   0.067961 -0.020563  0.062474  ...  0.124701  0.246099  0.240720   \n",
       "KLAC  0.048992  0.059905  0.135723  ...  0.214645  0.406202  0.434366   \n",
       "UNT   0.066843  0.174611  0.407000  ...  0.588566  0.406587  0.323144   \n",
       "WATT  0.038084  0.030054  0.088911  ...  0.167496  0.163125  0.163022   \n",
       "AVGR -0.000607  0.047128  0.023644  ...  0.043290  0.025630  0.088029   \n",
       "DEF   0.090888  0.166888  0.241814  ...  0.447933  0.632359  0.668545   \n",
       "VIPS  0.118901  0.076925  0.112553  ...  0.206245  0.335226  0.314515   \n",
       "CEI  -0.039738  0.051251  0.171021  ...  0.158683  0.054979  0.048295   \n",
       "FXA   0.049475  0.125636  0.211368  ...  0.296863  0.571735  0.314166   \n",
       "UTHR -0.002817  0.091714  0.063821  ...  0.198677  0.260207  0.290054   \n",
       "MIK   0.050916  0.087998  0.137953  ...  0.266907  0.292900  0.311491   \n",
       "EXK   0.061561  0.029851  0.170491  ...  0.194818  0.268437  0.046252   \n",
       "CMA   0.044038  0.181688  0.198468  ...  0.392829  0.466158  0.491216   \n",
       "SNOA -0.000001  0.077501  0.083089  ...  0.143166  0.086576  0.137016   \n",
       "BOTJ  0.028354  0.022388 -0.036160  ...  0.057431  0.031457  0.086401   \n",
       "AIR   0.037308  0.176902  0.226487  ...  0.278841  0.362387  0.393758   \n",
       "GER   0.149547  0.209557  0.384791  ...  1.000000  0.467148  0.446534   \n",
       "DVYE  0.080735  0.163020  0.304740  ...  0.467148  1.000000  0.592029   \n",
       "GAM   0.053558  0.120953  0.212286  ...  0.446534  0.592029  1.000000   \n",
       "AY    0.063280  0.139755  0.132744  ...  0.310832  0.303620  0.283000   \n",
       "LAC   0.077096  0.110883  0.101404  ...  0.183449  0.208867  0.144721   \n",
       "NKSH  0.073506  0.091549  0.118872  ...  0.175788  0.239941  0.253973   \n",
       "EME   0.056087  0.152449  0.201675  ...  0.339478  0.405154  0.446146   \n",
       "BBDO -0.019714  0.057738  0.148910  ...  0.168689  0.373606  0.190536   \n",
       "GRIF  0.083590  0.020015 -0.009387  ...  0.091420  0.099811  0.127072   \n",
       "IMGN  0.042534  0.066018  0.080556  ...  0.141021  0.182622  0.197384   \n",
       "\n",
       "            AY       LAC      NKSH       EME      BBDO      GRIF      IMGN  \n",
       "DF    0.059253  0.013526  0.123530  0.116517  0.069471  0.022214  0.045443  \n",
       "SQBG  0.115473  0.056405  0.167408  0.230055  0.113140  0.154118  0.028745  \n",
       "C     0.246211  0.189167  0.330709  0.481906  0.182026  0.143624  0.223703  \n",
       "PPC   0.136715  0.032140  0.132911  0.249026  0.132804  0.060087  0.037325  \n",
       "VOD   0.183211  0.101225  0.148344  0.255465  0.144951  0.048907  0.155452  \n",
       "TRUP  0.145081  0.097276  0.217666  0.243584  0.068564  0.076308  0.089468  \n",
       "NATI  0.168621  0.126861  0.230386  0.403664  0.162042  0.073413  0.161721  \n",
       "GNUS  0.063280  0.077096  0.073506  0.056087 -0.019714  0.083590  0.042534  \n",
       "RINF  0.139755  0.110883  0.091549  0.152449  0.057738  0.020015  0.066018  \n",
       "DMLP  0.132744  0.101404  0.118872  0.201675  0.148910 -0.009387  0.080556  \n",
       "NTES  0.064778  0.104337  0.065146  0.192172  0.131301  0.064507  0.144551  \n",
       "EMD   0.195391  0.145178  0.105937  0.198976  0.151878  0.151305  0.107066  \n",
       "QMN   0.154724  0.087286  0.127749  0.164366  0.123853  0.077512  0.120099  \n",
       "EVFM -0.015333  0.008108 -0.029947  0.006777  0.023966  0.019171  0.046903  \n",
       "TGTX  0.153695  0.096685  0.125536  0.192032  0.069359  0.109745  0.244285  \n",
       "ATU   0.199417  0.166804  0.218071  0.479971  0.168863  0.124439  0.148138  \n",
       "BTX   0.152602  0.161866  0.209665  0.256747  0.130042  0.085556  0.221017  \n",
       "CYTK  0.098130  0.110309  0.142934  0.227568  0.065549  0.083965  0.223017  \n",
       "TUSA  0.225026  0.173053  0.274057  0.451863  0.181451  0.118798  0.227751  \n",
       "HEWG  0.241490  0.221676  0.318885  0.481660  0.157864  0.106048  0.191722  \n",
       "FRPH  0.129369  0.164924  0.277878  0.302945  0.118678  0.096547  0.091925  \n",
       "ATNM  0.118061  0.132194  0.049542  0.129684  0.041530  0.058843  0.047156  \n",
       "UBFO  0.062323  0.032127  0.131986  0.113483  0.094348  0.093482  0.035911  \n",
       "FIVN  0.139544  0.079487  0.140948  0.245787  0.084515  0.084328  0.148796  \n",
       "PEG   0.197653  0.036505  0.041385  0.079816  0.093074  0.011771 -0.003474  \n",
       "KLAC  0.120923  0.124602  0.184808  0.350513  0.098451  0.017188  0.205949  \n",
       "UNT   0.259230  0.193528  0.154522  0.299601  0.165169  0.116499  0.121088  \n",
       "WATT  0.058825  0.108571  0.109206  0.144329  0.089944  0.045934  0.120415  \n",
       "AVGR  0.002737  0.007887  0.119533  0.068010  0.009188  0.039583  0.071067  \n",
       "DEF   0.269358  0.191405  0.284225  0.503433  0.210915  0.084051  0.185421  \n",
       "VIPS  0.095120  0.110733  0.078509  0.241571  0.097961  0.047289  0.170534  \n",
       "CEI   0.063058  0.026491  0.010128  0.055442  0.012619  0.032325  0.027552  \n",
       "FXA   0.156116  0.160129  0.106929  0.211595  0.220596 -0.006677  0.091933  \n",
       "UTHR  0.147013  0.108058  0.140727  0.287345  0.074093  0.101162  0.216258  \n",
       "MIK   0.192239  0.142697  0.097453  0.280671  0.098367  0.071400  0.178621  \n",
       "EXK   0.115376  0.095853  0.065496  0.023086  0.134894  0.047765  0.027007  \n",
       "CMA   0.205492  0.170726  0.334183  0.464065  0.152544  0.159793  0.153563  \n",
       "SNOA  0.086707  0.010204  0.065073  0.061300  0.066829  0.028434  0.019553  \n",
       "BOTJ  0.037364 -0.018689  0.029828  0.020327 -0.010179  0.047151 -0.002841  \n",
       "AIR   0.195208  0.138018  0.271175  0.426088  0.170690  0.097361  0.161841  \n",
       "GER   0.310832  0.183449  0.175788  0.339478  0.168689  0.091420  0.141021  \n",
       "DVYE  0.303620  0.208867  0.239941  0.405154  0.373606  0.099811  0.182622  \n",
       "GAM   0.283000  0.144721  0.253973  0.446146  0.190536  0.127072  0.197384  \n",
       "AY    1.000000  0.153110  0.137223  0.155926  0.105611  0.105512  0.109073  \n",
       "LAC   0.153110  1.000000  0.102443  0.110697  0.051578  0.060029  0.073254  \n",
       "NKSH  0.137223  0.102443  1.000000  0.302054  0.125397  0.094005  0.108091  \n",
       "EME   0.155926  0.110697  0.302054  1.000000  0.159480  0.089861  0.144744  \n",
       "BBDO  0.105611  0.051578  0.125397  0.159480  1.000000  0.037893  0.049618  \n",
       "GRIF  0.105512  0.060029  0.094005  0.089861  0.037893  1.000000  0.022069  \n",
       "IMGN  0.109073  0.073254  0.108091  0.144744  0.049618  0.022069  1.000000  \n",
       "\n",
       "[50 rows x 50 columns]"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr = log_ret.corr() #correlation matrix (dataframe) of log returns\n",
    "corr"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Computing the Distance Matrix\n",
    "\n",
    "Computed outside of Kruskal function since algorithm should be universal to all undirected weighted graphs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DF</th>\n",
       "      <th>SQBG</th>\n",
       "      <th>C</th>\n",
       "      <th>PPC</th>\n",
       "      <th>VOD</th>\n",
       "      <th>TRUP</th>\n",
       "      <th>NATI</th>\n",
       "      <th>GNUS</th>\n",
       "      <th>RINF</th>\n",
       "      <th>DMLP</th>\n",
       "      <th>...</th>\n",
       "      <th>GER</th>\n",
       "      <th>DVYE</th>\n",
       "      <th>GAM</th>\n",
       "      <th>AY</th>\n",
       "      <th>LAC</th>\n",
       "      <th>NKSH</th>\n",
       "      <th>EME</th>\n",
       "      <th>BBDO</th>\n",
       "      <th>GRIF</th>\n",
       "      <th>IMGN</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>DF</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.315831</td>\n",
       "      <td>1.328244</td>\n",
       "      <td>1.276388</td>\n",
       "      <td>1.315531</td>\n",
       "      <td>1.362149</td>\n",
       "      <td>1.357144</td>\n",
       "      <td>1.371249</td>\n",
       "      <td>1.392399</td>\n",
       "      <td>1.354748</td>\n",
       "      <td>...</td>\n",
       "      <td>1.333497</td>\n",
       "      <td>1.344783</td>\n",
       "      <td>1.294530</td>\n",
       "      <td>1.371675</td>\n",
       "      <td>1.404617</td>\n",
       "      <td>1.323986</td>\n",
       "      <td>1.329272</td>\n",
       "      <td>1.364206</td>\n",
       "      <td>1.398417</td>\n",
       "      <td>1.381707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SQBG</th>\n",
       "      <td>1.315831</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.273912</td>\n",
       "      <td>1.361426</td>\n",
       "      <td>1.352393</td>\n",
       "      <td>1.307691</td>\n",
       "      <td>1.296498</td>\n",
       "      <td>1.351607</td>\n",
       "      <td>1.337602</td>\n",
       "      <td>1.318924</td>\n",
       "      <td>...</td>\n",
       "      <td>1.295933</td>\n",
       "      <td>1.282867</td>\n",
       "      <td>1.276895</td>\n",
       "      <td>1.330058</td>\n",
       "      <td>1.373751</td>\n",
       "      <td>1.290420</td>\n",
       "      <td>1.240923</td>\n",
       "      <td>1.331810</td>\n",
       "      <td>1.300679</td>\n",
       "      <td>1.393739</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>1.328244</td>\n",
       "      <td>1.273912</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.268220</td>\n",
       "      <td>1.093645</td>\n",
       "      <td>1.224037</td>\n",
       "      <td>1.132437</td>\n",
       "      <td>1.349763</td>\n",
       "      <td>1.259024</td>\n",
       "      <td>1.273361</td>\n",
       "      <td>...</td>\n",
       "      <td>1.073443</td>\n",
       "      <td>0.960038</td>\n",
       "      <td>0.900669</td>\n",
       "      <td>1.227835</td>\n",
       "      <td>1.273446</td>\n",
       "      <td>1.156971</td>\n",
       "      <td>1.017933</td>\n",
       "      <td>1.279042</td>\n",
       "      <td>1.308721</td>\n",
       "      <td>1.246031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PPC</th>\n",
       "      <td>1.276388</td>\n",
       "      <td>1.361426</td>\n",
       "      <td>1.268220</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.250854</td>\n",
       "      <td>1.341001</td>\n",
       "      <td>1.296043</td>\n",
       "      <td>1.380031</td>\n",
       "      <td>1.344272</td>\n",
       "      <td>1.339532</td>\n",
       "      <td>...</td>\n",
       "      <td>1.304278</td>\n",
       "      <td>1.226750</td>\n",
       "      <td>1.235760</td>\n",
       "      <td>1.313990</td>\n",
       "      <td>1.391301</td>\n",
       "      <td>1.316882</td>\n",
       "      <td>1.225540</td>\n",
       "      <td>1.316963</td>\n",
       "      <td>1.371067</td>\n",
       "      <td>1.387570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VOD</th>\n",
       "      <td>1.315531</td>\n",
       "      <td>1.352393</td>\n",
       "      <td>1.093645</td>\n",
       "      <td>1.250854</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.375030</td>\n",
       "      <td>1.245146</td>\n",
       "      <td>1.334415</td>\n",
       "      <td>1.347617</td>\n",
       "      <td>1.323696</td>\n",
       "      <td>...</td>\n",
       "      <td>1.181531</td>\n",
       "      <td>1.038823</td>\n",
       "      <td>1.094573</td>\n",
       "      <td>1.278115</td>\n",
       "      <td>1.340728</td>\n",
       "      <td>1.305110</td>\n",
       "      <td>1.220275</td>\n",
       "      <td>1.307707</td>\n",
       "      <td>1.379197</td>\n",
       "      <td>1.299652</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TRUP</th>\n",
       "      <td>1.362149</td>\n",
       "      <td>1.307691</td>\n",
       "      <td>1.224037</td>\n",
       "      <td>1.341001</td>\n",
       "      <td>1.375030</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.254351</td>\n",
       "      <td>1.417175</td>\n",
       "      <td>1.365208</td>\n",
       "      <td>1.350913</td>\n",
       "      <td>...</td>\n",
       "      <td>1.312782</td>\n",
       "      <td>1.261004</td>\n",
       "      <td>1.233158</td>\n",
       "      <td>1.307607</td>\n",
       "      <td>1.343669</td>\n",
       "      <td>1.250867</td>\n",
       "      <td>1.229973</td>\n",
       "      <td>1.364871</td>\n",
       "      <td>1.359185</td>\n",
       "      <td>1.349468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NATI</th>\n",
       "      <td>1.357144</td>\n",
       "      <td>1.296498</td>\n",
       "      <td>1.132437</td>\n",
       "      <td>1.296043</td>\n",
       "      <td>1.245146</td>\n",
       "      <td>1.254351</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.396013</td>\n",
       "      <td>1.359526</td>\n",
       "      <td>1.310643</td>\n",
       "      <td>...</td>\n",
       "      <td>1.237878</td>\n",
       "      <td>1.127952</td>\n",
       "      <td>1.098288</td>\n",
       "      <td>1.289480</td>\n",
       "      <td>1.321468</td>\n",
       "      <td>1.240656</td>\n",
       "      <td>1.092095</td>\n",
       "      <td>1.294572</td>\n",
       "      <td>1.361314</td>\n",
       "      <td>1.294820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GNUS</th>\n",
       "      <td>1.371249</td>\n",
       "      <td>1.351607</td>\n",
       "      <td>1.349763</td>\n",
       "      <td>1.380031</td>\n",
       "      <td>1.334415</td>\n",
       "      <td>1.417175</td>\n",
       "      <td>1.396013</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.390259</td>\n",
       "      <td>1.380223</td>\n",
       "      <td>...</td>\n",
       "      <td>1.304188</td>\n",
       "      <td>1.355924</td>\n",
       "      <td>1.375821</td>\n",
       "      <td>1.368737</td>\n",
       "      <td>1.358605</td>\n",
       "      <td>1.361245</td>\n",
       "      <td>1.373982</td>\n",
       "      <td>1.428086</td>\n",
       "      <td>1.353817</td>\n",
       "      <td>1.383810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RINF</th>\n",
       "      <td>1.392399</td>\n",
       "      <td>1.337602</td>\n",
       "      <td>1.259024</td>\n",
       "      <td>1.344272</td>\n",
       "      <td>1.347617</td>\n",
       "      <td>1.365208</td>\n",
       "      <td>1.359526</td>\n",
       "      <td>1.390259</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.330342</td>\n",
       "      <td>...</td>\n",
       "      <td>1.257333</td>\n",
       "      <td>1.293816</td>\n",
       "      <td>1.325931</td>\n",
       "      <td>1.311674</td>\n",
       "      <td>1.333504</td>\n",
       "      <td>1.347925</td>\n",
       "      <td>1.301961</td>\n",
       "      <td>1.372779</td>\n",
       "      <td>1.399989</td>\n",
       "      <td>1.366735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DMLP</th>\n",
       "      <td>1.354748</td>\n",
       "      <td>1.318924</td>\n",
       "      <td>1.273361</td>\n",
       "      <td>1.339532</td>\n",
       "      <td>1.323696</td>\n",
       "      <td>1.350913</td>\n",
       "      <td>1.310643</td>\n",
       "      <td>1.380223</td>\n",
       "      <td>1.330342</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.109242</td>\n",
       "      <td>1.179203</td>\n",
       "      <td>1.255160</td>\n",
       "      <td>1.317009</td>\n",
       "      <td>1.340594</td>\n",
       "      <td>1.327500</td>\n",
       "      <td>1.263586</td>\n",
       "      <td>1.304677</td>\n",
       "      <td>1.420836</td>\n",
       "      <td>1.356056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NTES</th>\n",
       "      <td>1.409112</td>\n",
       "      <td>1.386497</td>\n",
       "      <td>1.233636</td>\n",
       "      <td>1.354532</td>\n",
       "      <td>1.230854</td>\n",
       "      <td>1.341441</td>\n",
       "      <td>1.258595</td>\n",
       "      <td>1.370103</td>\n",
       "      <td>1.374489</td>\n",
       "      <td>1.371129</td>\n",
       "      <td>...</td>\n",
       "      <td>1.286188</td>\n",
       "      <td>1.096318</td>\n",
       "      <td>1.201492</td>\n",
       "      <td>1.367642</td>\n",
       "      <td>1.338405</td>\n",
       "      <td>1.367372</td>\n",
       "      <td>1.271085</td>\n",
       "      <td>1.318104</td>\n",
       "      <td>1.367840</td>\n",
       "      <td>1.308013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EMD</th>\n",
       "      <td>1.368753</td>\n",
       "      <td>1.333343</td>\n",
       "      <td>1.209980</td>\n",
       "      <td>1.292107</td>\n",
       "      <td>1.215383</td>\n",
       "      <td>1.347692</td>\n",
       "      <td>1.306719</td>\n",
       "      <td>1.372539</td>\n",
       "      <td>1.328126</td>\n",
       "      <td>1.261902</td>\n",
       "      <td>...</td>\n",
       "      <td>1.090142</td>\n",
       "      <td>1.051113</td>\n",
       "      <td>1.096903</td>\n",
       "      <td>1.268549</td>\n",
       "      <td>1.307533</td>\n",
       "      <td>1.337209</td>\n",
       "      <td>1.265720</td>\n",
       "      <td>1.302400</td>\n",
       "      <td>1.302839</td>\n",
       "      <td>1.336363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>QMN</th>\n",
       "      <td>1.346513</td>\n",
       "      <td>1.337603</td>\n",
       "      <td>1.304054</td>\n",
       "      <td>1.345989</td>\n",
       "      <td>1.281007</td>\n",
       "      <td>1.311021</td>\n",
       "      <td>1.273693</td>\n",
       "      <td>1.340338</td>\n",
       "      <td>1.349149</td>\n",
       "      <td>1.303966</td>\n",
       "      <td>...</td>\n",
       "      <td>1.239090</td>\n",
       "      <td>1.218023</td>\n",
       "      <td>1.183279</td>\n",
       "      <td>1.300212</td>\n",
       "      <td>1.351084</td>\n",
       "      <td>1.320796</td>\n",
       "      <td>1.292775</td>\n",
       "      <td>1.323743</td>\n",
       "      <td>1.358299</td>\n",
       "      <td>1.326575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EVFM</th>\n",
       "      <td>1.393899</td>\n",
       "      <td>1.385622</td>\n",
       "      <td>1.402563</td>\n",
       "      <td>1.421368</td>\n",
       "      <td>1.381045</td>\n",
       "      <td>1.406295</td>\n",
       "      <td>1.403904</td>\n",
       "      <td>1.398399</td>\n",
       "      <td>1.449318</td>\n",
       "      <td>1.391662</td>\n",
       "      <td>...</td>\n",
       "      <td>1.384900</td>\n",
       "      <td>1.415307</td>\n",
       "      <td>1.393752</td>\n",
       "      <td>1.425014</td>\n",
       "      <td>1.408469</td>\n",
       "      <td>1.435233</td>\n",
       "      <td>1.409413</td>\n",
       "      <td>1.397165</td>\n",
       "      <td>1.400592</td>\n",
       "      <td>1.380650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TGTX</th>\n",
       "      <td>1.384723</td>\n",
       "      <td>1.296169</td>\n",
       "      <td>1.242676</td>\n",
       "      <td>1.364260</td>\n",
       "      <td>1.323333</td>\n",
       "      <td>1.295656</td>\n",
       "      <td>1.280871</td>\n",
       "      <td>1.369878</td>\n",
       "      <td>1.346539</td>\n",
       "      <td>1.361311</td>\n",
       "      <td>...</td>\n",
       "      <td>1.272543</td>\n",
       "      <td>1.232470</td>\n",
       "      <td>1.228533</td>\n",
       "      <td>1.301004</td>\n",
       "      <td>1.344109</td>\n",
       "      <td>1.322470</td>\n",
       "      <td>1.271195</td>\n",
       "      <td>1.364288</td>\n",
       "      <td>1.334357</td>\n",
       "      <td>1.229402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ATU</th>\n",
       "      <td>1.319998</td>\n",
       "      <td>1.284238</td>\n",
       "      <td>1.028932</td>\n",
       "      <td>1.237310</td>\n",
       "      <td>1.206692</td>\n",
       "      <td>1.249363</td>\n",
       "      <td>1.142608</td>\n",
       "      <td>1.376660</td>\n",
       "      <td>1.320284</td>\n",
       "      <td>1.204098</td>\n",
       "      <td>...</td>\n",
       "      <td>1.113167</td>\n",
       "      <td>1.049030</td>\n",
       "      <td>1.051130</td>\n",
       "      <td>1.265372</td>\n",
       "      <td>1.290888</td>\n",
       "      <td>1.250543</td>\n",
       "      <td>1.019832</td>\n",
       "      <td>1.289292</td>\n",
       "      <td>1.323300</td>\n",
       "      <td>1.305267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BTX</th>\n",
       "      <td>1.402912</td>\n",
       "      <td>1.340666</td>\n",
       "      <td>1.214178</td>\n",
       "      <td>1.336390</td>\n",
       "      <td>1.279417</td>\n",
       "      <td>1.274968</td>\n",
       "      <td>1.250312</td>\n",
       "      <td>1.396645</td>\n",
       "      <td>1.339611</td>\n",
       "      <td>1.350809</td>\n",
       "      <td>...</td>\n",
       "      <td>1.256337</td>\n",
       "      <td>1.217687</td>\n",
       "      <td>1.248358</td>\n",
       "      <td>1.301843</td>\n",
       "      <td>1.294707</td>\n",
       "      <td>1.257247</td>\n",
       "      <td>1.219223</td>\n",
       "      <td>1.319059</td>\n",
       "      <td>1.352364</td>\n",
       "      <td>1.248185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CYTK</th>\n",
       "      <td>1.347784</td>\n",
       "      <td>1.362697</td>\n",
       "      <td>1.274688</td>\n",
       "      <td>1.354378</td>\n",
       "      <td>1.320663</td>\n",
       "      <td>1.286321</td>\n",
       "      <td>1.303765</td>\n",
       "      <td>1.348820</td>\n",
       "      <td>1.398223</td>\n",
       "      <td>1.359404</td>\n",
       "      <td>...</td>\n",
       "      <td>1.296619</td>\n",
       "      <td>1.303166</td>\n",
       "      <td>1.250677</td>\n",
       "      <td>1.343034</td>\n",
       "      <td>1.333935</td>\n",
       "      <td>1.309249</td>\n",
       "      <td>1.242926</td>\n",
       "      <td>1.367078</td>\n",
       "      <td>1.353540</td>\n",
       "      <td>1.246582</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TUSA</th>\n",
       "      <td>1.296503</td>\n",
       "      <td>1.266353</td>\n",
       "      <td>0.949941</td>\n",
       "      <td>1.242425</td>\n",
       "      <td>1.147206</td>\n",
       "      <td>1.237573</td>\n",
       "      <td>1.110229</td>\n",
       "      <td>1.379098</td>\n",
       "      <td>1.263951</td>\n",
       "      <td>1.251722</td>\n",
       "      <td>...</td>\n",
       "      <td>1.038677</td>\n",
       "      <td>1.006315</td>\n",
       "      <td>0.914362</td>\n",
       "      <td>1.244969</td>\n",
       "      <td>1.286038</td>\n",
       "      <td>1.204942</td>\n",
       "      <td>1.047031</td>\n",
       "      <td>1.279491</td>\n",
       "      <td>1.327555</td>\n",
       "      <td>1.242779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HEWG</th>\n",
       "      <td>1.299288</td>\n",
       "      <td>1.277875</td>\n",
       "      <td>0.815832</td>\n",
       "      <td>1.253726</td>\n",
       "      <td>0.994422</td>\n",
       "      <td>1.215887</td>\n",
       "      <td>1.089368</td>\n",
       "      <td>1.363820</td>\n",
       "      <td>1.276640</td>\n",
       "      <td>1.261164</td>\n",
       "      <td>...</td>\n",
       "      <td>1.123287</td>\n",
       "      <td>0.878540</td>\n",
       "      <td>0.861420</td>\n",
       "      <td>1.231673</td>\n",
       "      <td>1.247657</td>\n",
       "      <td>1.167146</td>\n",
       "      <td>1.018174</td>\n",
       "      <td>1.297795</td>\n",
       "      <td>1.337125</td>\n",
       "      <td>1.271439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FRPH</th>\n",
       "      <td>1.348607</td>\n",
       "      <td>1.291971</td>\n",
       "      <td>1.239602</td>\n",
       "      <td>1.313323</td>\n",
       "      <td>1.317865</td>\n",
       "      <td>1.247835</td>\n",
       "      <td>1.251962</td>\n",
       "      <td>1.407373</td>\n",
       "      <td>1.345107</td>\n",
       "      <td>1.350224</td>\n",
       "      <td>...</td>\n",
       "      <td>1.286932</td>\n",
       "      <td>1.239263</td>\n",
       "      <td>1.232577</td>\n",
       "      <td>1.319569</td>\n",
       "      <td>1.292344</td>\n",
       "      <td>1.201767</td>\n",
       "      <td>1.180724</td>\n",
       "      <td>1.327646</td>\n",
       "      <td>1.344212</td>\n",
       "      <td>1.347646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ATNM</th>\n",
       "      <td>1.355064</td>\n",
       "      <td>1.337373</td>\n",
       "      <td>1.263846</td>\n",
       "      <td>1.353589</td>\n",
       "      <td>1.352719</td>\n",
       "      <td>1.309088</td>\n",
       "      <td>1.334211</td>\n",
       "      <td>1.404966</td>\n",
       "      <td>1.356373</td>\n",
       "      <td>1.314840</td>\n",
       "      <td>...</td>\n",
       "      <td>1.269468</td>\n",
       "      <td>1.306591</td>\n",
       "      <td>1.279425</td>\n",
       "      <td>1.328110</td>\n",
       "      <td>1.317426</td>\n",
       "      <td>1.378737</td>\n",
       "      <td>1.319331</td>\n",
       "      <td>1.384536</td>\n",
       "      <td>1.371974</td>\n",
       "      <td>1.380466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UBFO</th>\n",
       "      <td>1.378311</td>\n",
       "      <td>1.407838</td>\n",
       "      <td>1.308690</td>\n",
       "      <td>1.404994</td>\n",
       "      <td>1.400978</td>\n",
       "      <td>1.390308</td>\n",
       "      <td>1.362360</td>\n",
       "      <td>1.362908</td>\n",
       "      <td>1.401274</td>\n",
       "      <td>1.376451</td>\n",
       "      <td>...</td>\n",
       "      <td>1.383459</td>\n",
       "      <td>1.344418</td>\n",
       "      <td>1.340341</td>\n",
       "      <td>1.369436</td>\n",
       "      <td>1.391311</td>\n",
       "      <td>1.317584</td>\n",
       "      <td>1.331553</td>\n",
       "      <td>1.345847</td>\n",
       "      <td>1.346490</td>\n",
       "      <td>1.388588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FIVN</th>\n",
       "      <td>1.464232</td>\n",
       "      <td>1.298061</td>\n",
       "      <td>1.248607</td>\n",
       "      <td>1.353702</td>\n",
       "      <td>1.318298</td>\n",
       "      <td>1.225675</td>\n",
       "      <td>1.207969</td>\n",
       "      <td>1.437157</td>\n",
       "      <td>1.396388</td>\n",
       "      <td>1.329944</td>\n",
       "      <td>...</td>\n",
       "      <td>1.303536</td>\n",
       "      <td>1.222485</td>\n",
       "      <td>1.176771</td>\n",
       "      <td>1.311836</td>\n",
       "      <td>1.356844</td>\n",
       "      <td>1.310764</td>\n",
       "      <td>1.228180</td>\n",
       "      <td>1.353134</td>\n",
       "      <td>1.353271</td>\n",
       "      <td>1.304764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PEG</th>\n",
       "      <td>1.320373</td>\n",
       "      <td>1.388747</td>\n",
       "      <td>1.378847</td>\n",
       "      <td>1.261317</td>\n",
       "      <td>1.267486</td>\n",
       "      <td>1.358975</td>\n",
       "      <td>1.356219</td>\n",
       "      <td>1.365312</td>\n",
       "      <td>1.428680</td>\n",
       "      <td>1.369326</td>\n",
       "      <td>...</td>\n",
       "      <td>1.323102</td>\n",
       "      <td>1.227926</td>\n",
       "      <td>1.232299</td>\n",
       "      <td>1.266765</td>\n",
       "      <td>1.388160</td>\n",
       "      <td>1.384641</td>\n",
       "      <td>1.356602</td>\n",
       "      <td>1.346793</td>\n",
       "      <td>1.405866</td>\n",
       "      <td>1.416668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KLAC</th>\n",
       "      <td>1.359902</td>\n",
       "      <td>1.297062</td>\n",
       "      <td>1.137704</td>\n",
       "      <td>1.278501</td>\n",
       "      <td>1.261196</td>\n",
       "      <td>1.255603</td>\n",
       "      <td>1.143870</td>\n",
       "      <td>1.379136</td>\n",
       "      <td>1.371200</td>\n",
       "      <td>1.314745</td>\n",
       "      <td>...</td>\n",
       "      <td>1.253279</td>\n",
       "      <td>1.089768</td>\n",
       "      <td>1.063611</td>\n",
       "      <td>1.325954</td>\n",
       "      <td>1.323176</td>\n",
       "      <td>1.276865</td>\n",
       "      <td>1.139725</td>\n",
       "      <td>1.342795</td>\n",
       "      <td>1.402007</td>\n",
       "      <td>1.260199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UNT</th>\n",
       "      <td>1.369433</td>\n",
       "      <td>1.317702</td>\n",
       "      <td>1.127092</td>\n",
       "      <td>1.323670</td>\n",
       "      <td>1.272766</td>\n",
       "      <td>1.320302</td>\n",
       "      <td>1.263555</td>\n",
       "      <td>1.366131</td>\n",
       "      <td>1.284826</td>\n",
       "      <td>1.089036</td>\n",
       "      <td>...</td>\n",
       "      <td>0.907121</td>\n",
       "      <td>1.089415</td>\n",
       "      <td>1.163492</td>\n",
       "      <td>1.217185</td>\n",
       "      <td>1.270017</td>\n",
       "      <td>1.300368</td>\n",
       "      <td>1.183553</td>\n",
       "      <td>1.292154</td>\n",
       "      <td>1.329287</td>\n",
       "      <td>1.325829</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WATT</th>\n",
       "      <td>1.359694</td>\n",
       "      <td>1.396771</td>\n",
       "      <td>1.296411</td>\n",
       "      <td>1.368912</td>\n",
       "      <td>1.340195</td>\n",
       "      <td>1.371638</td>\n",
       "      <td>1.319797</td>\n",
       "      <td>1.387022</td>\n",
       "      <td>1.392800</td>\n",
       "      <td>1.349881</td>\n",
       "      <td>...</td>\n",
       "      <td>1.290352</td>\n",
       "      <td>1.293735</td>\n",
       "      <td>1.293815</td>\n",
       "      <td>1.371988</td>\n",
       "      <td>1.335237</td>\n",
       "      <td>1.334762</td>\n",
       "      <td>1.308182</td>\n",
       "      <td>1.349115</td>\n",
       "      <td>1.381351</td>\n",
       "      <td>1.326337</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AVGR</th>\n",
       "      <td>1.443166</td>\n",
       "      <td>1.369277</td>\n",
       "      <td>1.364796</td>\n",
       "      <td>1.404079</td>\n",
       "      <td>1.383054</td>\n",
       "      <td>1.356614</td>\n",
       "      <td>1.366163</td>\n",
       "      <td>1.414643</td>\n",
       "      <td>1.380487</td>\n",
       "      <td>1.397394</td>\n",
       "      <td>...</td>\n",
       "      <td>1.383264</td>\n",
       "      <td>1.395972</td>\n",
       "      <td>1.350534</td>\n",
       "      <td>1.412277</td>\n",
       "      <td>1.408626</td>\n",
       "      <td>1.327002</td>\n",
       "      <td>1.365276</td>\n",
       "      <td>1.407702</td>\n",
       "      <td>1.385942</td>\n",
       "      <td>1.363035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DEF</th>\n",
       "      <td>1.267071</td>\n",
       "      <td>1.252082</td>\n",
       "      <td>0.948921</td>\n",
       "      <td>1.157007</td>\n",
       "      <td>1.074623</td>\n",
       "      <td>1.174504</td>\n",
       "      <td>1.046542</td>\n",
       "      <td>1.348416</td>\n",
       "      <td>1.290823</td>\n",
       "      <td>1.231411</td>\n",
       "      <td>...</td>\n",
       "      <td>1.050778</td>\n",
       "      <td>0.857485</td>\n",
       "      <td>0.814193</td>\n",
       "      <td>1.208836</td>\n",
       "      <td>1.271688</td>\n",
       "      <td>1.196474</td>\n",
       "      <td>0.996561</td>\n",
       "      <td>1.256252</td>\n",
       "      <td>1.353476</td>\n",
       "      <td>1.276384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VIPS</th>\n",
       "      <td>1.382940</td>\n",
       "      <td>1.362381</td>\n",
       "      <td>1.209026</td>\n",
       "      <td>1.310800</td>\n",
       "      <td>1.253726</td>\n",
       "      <td>1.319568</td>\n",
       "      <td>1.276507</td>\n",
       "      <td>1.327478</td>\n",
       "      <td>1.358731</td>\n",
       "      <td>1.332251</td>\n",
       "      <td>...</td>\n",
       "      <td>1.259965</td>\n",
       "      <td>1.153060</td>\n",
       "      <td>1.170884</td>\n",
       "      <td>1.345273</td>\n",
       "      <td>1.333617</td>\n",
       "      <td>1.357565</td>\n",
       "      <td>1.231608</td>\n",
       "      <td>1.343160</td>\n",
       "      <td>1.380370</td>\n",
       "      <td>1.287995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CEI</th>\n",
       "      <td>1.397165</td>\n",
       "      <td>1.358246</td>\n",
       "      <td>1.399399</td>\n",
       "      <td>1.383800</td>\n",
       "      <td>1.391132</td>\n",
       "      <td>1.419795</td>\n",
       "      <td>1.387345</td>\n",
       "      <td>1.442039</td>\n",
       "      <td>1.377497</td>\n",
       "      <td>1.287617</td>\n",
       "      <td>...</td>\n",
       "      <td>1.297164</td>\n",
       "      <td>1.374788</td>\n",
       "      <td>1.379642</td>\n",
       "      <td>1.368899</td>\n",
       "      <td>1.395356</td>\n",
       "      <td>1.407034</td>\n",
       "      <td>1.374451</td>\n",
       "      <td>1.405262</td>\n",
       "      <td>1.391169</td>\n",
       "      <td>1.394595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FXA</th>\n",
       "      <td>1.387766</td>\n",
       "      <td>1.350728</td>\n",
       "      <td>1.227833</td>\n",
       "      <td>1.274204</td>\n",
       "      <td>1.189893</td>\n",
       "      <td>1.355306</td>\n",
       "      <td>1.273140</td>\n",
       "      <td>1.378786</td>\n",
       "      <td>1.322395</td>\n",
       "      <td>1.255891</td>\n",
       "      <td>...</td>\n",
       "      <td>1.185864</td>\n",
       "      <td>0.925489</td>\n",
       "      <td>1.171182</td>\n",
       "      <td>1.299141</td>\n",
       "      <td>1.296048</td>\n",
       "      <td>1.336467</td>\n",
       "      <td>1.255711</td>\n",
       "      <td>1.248522</td>\n",
       "      <td>1.418927</td>\n",
       "      <td>1.347640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UTHR</th>\n",
       "      <td>1.304650</td>\n",
       "      <td>1.273688</td>\n",
       "      <td>1.161793</td>\n",
       "      <td>1.317108</td>\n",
       "      <td>1.315681</td>\n",
       "      <td>1.268911</td>\n",
       "      <td>1.266462</td>\n",
       "      <td>1.416204</td>\n",
       "      <td>1.347803</td>\n",
       "      <td>1.368342</td>\n",
       "      <td>...</td>\n",
       "      <td>1.265956</td>\n",
       "      <td>1.216382</td>\n",
       "      <td>1.191592</td>\n",
       "      <td>1.306129</td>\n",
       "      <td>1.335621</td>\n",
       "      <td>1.310933</td>\n",
       "      <td>1.193863</td>\n",
       "      <td>1.360814</td>\n",
       "      <td>1.340775</td>\n",
       "      <td>1.251992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIK</th>\n",
       "      <td>1.321265</td>\n",
       "      <td>1.302021</td>\n",
       "      <td>1.159114</td>\n",
       "      <td>1.276571</td>\n",
       "      <td>1.254082</td>\n",
       "      <td>1.331459</td>\n",
       "      <td>1.284569</td>\n",
       "      <td>1.377741</td>\n",
       "      <td>1.350557</td>\n",
       "      <td>1.313047</td>\n",
       "      <td>...</td>\n",
       "      <td>1.210862</td>\n",
       "      <td>1.189201</td>\n",
       "      <td>1.173464</td>\n",
       "      <td>1.271032</td>\n",
       "      <td>1.309429</td>\n",
       "      <td>1.343538</td>\n",
       "      <td>1.199440</td>\n",
       "      <td>1.342858</td>\n",
       "      <td>1.362791</td>\n",
       "      <td>1.281701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EXK</th>\n",
       "      <td>1.395290</td>\n",
       "      <td>1.396734</td>\n",
       "      <td>1.429208</td>\n",
       "      <td>1.374524</td>\n",
       "      <td>1.350827</td>\n",
       "      <td>1.404960</td>\n",
       "      <td>1.366276</td>\n",
       "      <td>1.369992</td>\n",
       "      <td>1.392945</td>\n",
       "      <td>1.288029</td>\n",
       "      <td>...</td>\n",
       "      <td>1.269001</td>\n",
       "      <td>1.209598</td>\n",
       "      <td>1.381122</td>\n",
       "      <td>1.330131</td>\n",
       "      <td>1.344728</td>\n",
       "      <td>1.367117</td>\n",
       "      <td>1.397794</td>\n",
       "      <td>1.315376</td>\n",
       "      <td>1.380026</td>\n",
       "      <td>1.394986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CMA</th>\n",
       "      <td>1.332837</td>\n",
       "      <td>1.275873</td>\n",
       "      <td>0.688861</td>\n",
       "      <td>1.301617</td>\n",
       "      <td>1.151432</td>\n",
       "      <td>1.232582</td>\n",
       "      <td>1.155235</td>\n",
       "      <td>1.382724</td>\n",
       "      <td>1.279306</td>\n",
       "      <td>1.266121</td>\n",
       "      <td>...</td>\n",
       "      <td>1.101972</td>\n",
       "      <td>1.033288</td>\n",
       "      <td>1.008746</td>\n",
       "      <td>1.260562</td>\n",
       "      <td>1.287847</td>\n",
       "      <td>1.153965</td>\n",
       "      <td>1.035311</td>\n",
       "      <td>1.301888</td>\n",
       "      <td>1.296308</td>\n",
       "      <td>1.301105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SNOA</th>\n",
       "      <td>1.385213</td>\n",
       "      <td>1.366694</td>\n",
       "      <td>1.337497</td>\n",
       "      <td>1.381839</td>\n",
       "      <td>1.373399</td>\n",
       "      <td>1.408846</td>\n",
       "      <td>1.382782</td>\n",
       "      <td>1.414215</td>\n",
       "      <td>1.358307</td>\n",
       "      <td>1.354187</td>\n",
       "      <td>...</td>\n",
       "      <td>1.309071</td>\n",
       "      <td>1.351609</td>\n",
       "      <td>1.313761</td>\n",
       "      <td>1.351513</td>\n",
       "      <td>1.406980</td>\n",
       "      <td>1.367426</td>\n",
       "      <td>1.370183</td>\n",
       "      <td>1.366142</td>\n",
       "      <td>1.393962</td>\n",
       "      <td>1.400319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BOTJ</th>\n",
       "      <td>1.408182</td>\n",
       "      <td>1.427636</td>\n",
       "      <td>1.389511</td>\n",
       "      <td>1.412713</td>\n",
       "      <td>1.393012</td>\n",
       "      <td>1.427814</td>\n",
       "      <td>1.425151</td>\n",
       "      <td>1.394020</td>\n",
       "      <td>1.398294</td>\n",
       "      <td>1.439555</td>\n",
       "      <td>...</td>\n",
       "      <td>1.373003</td>\n",
       "      <td>1.391792</td>\n",
       "      <td>1.351739</td>\n",
       "      <td>1.387541</td>\n",
       "      <td>1.427367</td>\n",
       "      <td>1.392962</td>\n",
       "      <td>1.399766</td>\n",
       "      <td>1.421393</td>\n",
       "      <td>1.380470</td>\n",
       "      <td>1.416221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AIR</th>\n",
       "      <td>1.307711</td>\n",
       "      <td>1.276006</td>\n",
       "      <td>1.122179</td>\n",
       "      <td>1.275675</td>\n",
       "      <td>1.266999</td>\n",
       "      <td>1.264514</td>\n",
       "      <td>1.166649</td>\n",
       "      <td>1.387582</td>\n",
       "      <td>1.283042</td>\n",
       "      <td>1.243795</td>\n",
       "      <td>...</td>\n",
       "      <td>1.200966</td>\n",
       "      <td>1.129259</td>\n",
       "      <td>1.101129</td>\n",
       "      <td>1.268694</td>\n",
       "      <td>1.312998</td>\n",
       "      <td>1.207332</td>\n",
       "      <td>1.071365</td>\n",
       "      <td>1.287874</td>\n",
       "      <td>1.343606</td>\n",
       "      <td>1.294727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GER</th>\n",
       "      <td>1.333497</td>\n",
       "      <td>1.295933</td>\n",
       "      <td>1.073443</td>\n",
       "      <td>1.304278</td>\n",
       "      <td>1.181531</td>\n",
       "      <td>1.312782</td>\n",
       "      <td>1.237878</td>\n",
       "      <td>1.304188</td>\n",
       "      <td>1.257333</td>\n",
       "      <td>1.109242</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.032329</td>\n",
       "      <td>1.052108</td>\n",
       "      <td>1.174026</td>\n",
       "      <td>1.277929</td>\n",
       "      <td>1.283910</td>\n",
       "      <td>1.149367</td>\n",
       "      <td>1.289427</td>\n",
       "      <td>1.348020</td>\n",
       "      <td>1.310709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DVYE</th>\n",
       "      <td>1.344783</td>\n",
       "      <td>1.282867</td>\n",
       "      <td>0.960038</td>\n",
       "      <td>1.226750</td>\n",
       "      <td>1.038823</td>\n",
       "      <td>1.261004</td>\n",
       "      <td>1.127952</td>\n",
       "      <td>1.355924</td>\n",
       "      <td>1.293816</td>\n",
       "      <td>1.179203</td>\n",
       "      <td>...</td>\n",
       "      <td>1.032329</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.903295</td>\n",
       "      <td>1.180152</td>\n",
       "      <td>1.257882</td>\n",
       "      <td>1.232930</td>\n",
       "      <td>1.090730</td>\n",
       "      <td>1.119280</td>\n",
       "      <td>1.341781</td>\n",
       "      <td>1.278576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GAM</th>\n",
       "      <td>1.294530</td>\n",
       "      <td>1.276895</td>\n",
       "      <td>0.900669</td>\n",
       "      <td>1.235760</td>\n",
       "      <td>1.094573</td>\n",
       "      <td>1.233158</td>\n",
       "      <td>1.098288</td>\n",
       "      <td>1.375821</td>\n",
       "      <td>1.325931</td>\n",
       "      <td>1.255160</td>\n",
       "      <td>...</td>\n",
       "      <td>1.052108</td>\n",
       "      <td>0.903295</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.197497</td>\n",
       "      <td>1.307883</td>\n",
       "      <td>1.221497</td>\n",
       "      <td>1.052477</td>\n",
       "      <td>1.272371</td>\n",
       "      <td>1.321308</td>\n",
       "      <td>1.266978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AY</th>\n",
       "      <td>1.371675</td>\n",
       "      <td>1.330058</td>\n",
       "      <td>1.227835</td>\n",
       "      <td>1.313990</td>\n",
       "      <td>1.278115</td>\n",
       "      <td>1.307607</td>\n",
       "      <td>1.289480</td>\n",
       "      <td>1.368737</td>\n",
       "      <td>1.311674</td>\n",
       "      <td>1.317009</td>\n",
       "      <td>...</td>\n",
       "      <td>1.174026</td>\n",
       "      <td>1.180152</td>\n",
       "      <td>1.197497</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.301453</td>\n",
       "      <td>1.313603</td>\n",
       "      <td>1.299288</td>\n",
       "      <td>1.337452</td>\n",
       "      <td>1.337526</td>\n",
       "      <td>1.334861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LAC</th>\n",
       "      <td>1.404617</td>\n",
       "      <td>1.373751</td>\n",
       "      <td>1.273446</td>\n",
       "      <td>1.391301</td>\n",
       "      <td>1.340728</td>\n",
       "      <td>1.343669</td>\n",
       "      <td>1.321468</td>\n",
       "      <td>1.358605</td>\n",
       "      <td>1.333504</td>\n",
       "      <td>1.340594</td>\n",
       "      <td>...</td>\n",
       "      <td>1.277929</td>\n",
       "      <td>1.257882</td>\n",
       "      <td>1.307883</td>\n",
       "      <td>1.301453</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.339819</td>\n",
       "      <td>1.333644</td>\n",
       "      <td>1.377260</td>\n",
       "      <td>1.371110</td>\n",
       "      <td>1.361430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NKSH</th>\n",
       "      <td>1.323986</td>\n",
       "      <td>1.290420</td>\n",
       "      <td>1.156971</td>\n",
       "      <td>1.316882</td>\n",
       "      <td>1.305110</td>\n",
       "      <td>1.250867</td>\n",
       "      <td>1.240656</td>\n",
       "      <td>1.361245</td>\n",
       "      <td>1.347925</td>\n",
       "      <td>1.327500</td>\n",
       "      <td>...</td>\n",
       "      <td>1.283910</td>\n",
       "      <td>1.232930</td>\n",
       "      <td>1.221497</td>\n",
       "      <td>1.313603</td>\n",
       "      <td>1.339819</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.181479</td>\n",
       "      <td>1.322576</td>\n",
       "      <td>1.346102</td>\n",
       "      <td>1.335597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EME</th>\n",
       "      <td>1.329272</td>\n",
       "      <td>1.240923</td>\n",
       "      <td>1.017933</td>\n",
       "      <td>1.225540</td>\n",
       "      <td>1.220275</td>\n",
       "      <td>1.229973</td>\n",
       "      <td>1.092095</td>\n",
       "      <td>1.373982</td>\n",
       "      <td>1.301961</td>\n",
       "      <td>1.263586</td>\n",
       "      <td>...</td>\n",
       "      <td>1.149367</td>\n",
       "      <td>1.090730</td>\n",
       "      <td>1.052477</td>\n",
       "      <td>1.299288</td>\n",
       "      <td>1.333644</td>\n",
       "      <td>1.181479</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.296549</td>\n",
       "      <td>1.349177</td>\n",
       "      <td>1.307865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BBDO</th>\n",
       "      <td>1.364206</td>\n",
       "      <td>1.331810</td>\n",
       "      <td>1.279042</td>\n",
       "      <td>1.316963</td>\n",
       "      <td>1.307707</td>\n",
       "      <td>1.364871</td>\n",
       "      <td>1.294572</td>\n",
       "      <td>1.428086</td>\n",
       "      <td>1.372779</td>\n",
       "      <td>1.304677</td>\n",
       "      <td>...</td>\n",
       "      <td>1.289427</td>\n",
       "      <td>1.119280</td>\n",
       "      <td>1.272371</td>\n",
       "      <td>1.337452</td>\n",
       "      <td>1.377260</td>\n",
       "      <td>1.322576</td>\n",
       "      <td>1.296549</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.387160</td>\n",
       "      <td>1.378682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GRIF</th>\n",
       "      <td>1.398417</td>\n",
       "      <td>1.300679</td>\n",
       "      <td>1.308721</td>\n",
       "      <td>1.371067</td>\n",
       "      <td>1.379197</td>\n",
       "      <td>1.359185</td>\n",
       "      <td>1.361314</td>\n",
       "      <td>1.353817</td>\n",
       "      <td>1.399989</td>\n",
       "      <td>1.420836</td>\n",
       "      <td>...</td>\n",
       "      <td>1.348020</td>\n",
       "      <td>1.341781</td>\n",
       "      <td>1.321308</td>\n",
       "      <td>1.337526</td>\n",
       "      <td>1.371110</td>\n",
       "      <td>1.346102</td>\n",
       "      <td>1.349177</td>\n",
       "      <td>1.387160</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.398521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IMGN</th>\n",
       "      <td>1.381707</td>\n",
       "      <td>1.393739</td>\n",
       "      <td>1.246031</td>\n",
       "      <td>1.387570</td>\n",
       "      <td>1.299652</td>\n",
       "      <td>1.349468</td>\n",
       "      <td>1.294820</td>\n",
       "      <td>1.383810</td>\n",
       "      <td>1.366735</td>\n",
       "      <td>1.356056</td>\n",
       "      <td>...</td>\n",
       "      <td>1.310709</td>\n",
       "      <td>1.278576</td>\n",
       "      <td>1.266978</td>\n",
       "      <td>1.334861</td>\n",
       "      <td>1.361430</td>\n",
       "      <td>1.335597</td>\n",
       "      <td>1.307865</td>\n",
       "      <td>1.378682</td>\n",
       "      <td>1.398521</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>50 rows × 50 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            DF      SQBG         C       PPC       VOD      TRUP      NATI  \\\n",
       "DF    0.000000  1.315831  1.328244  1.276388  1.315531  1.362149  1.357144   \n",
       "SQBG  1.315831  0.000000  1.273912  1.361426  1.352393  1.307691  1.296498   \n",
       "C     1.328244  1.273912  0.000000  1.268220  1.093645  1.224037  1.132437   \n",
       "PPC   1.276388  1.361426  1.268220  0.000000  1.250854  1.341001  1.296043   \n",
       "VOD   1.315531  1.352393  1.093645  1.250854  0.000000  1.375030  1.245146   \n",
       "TRUP  1.362149  1.307691  1.224037  1.341001  1.375030  0.000000  1.254351   \n",
       "NATI  1.357144  1.296498  1.132437  1.296043  1.245146  1.254351  0.000000   \n",
       "GNUS  1.371249  1.351607  1.349763  1.380031  1.334415  1.417175  1.396013   \n",
       "RINF  1.392399  1.337602  1.259024  1.344272  1.347617  1.365208  1.359526   \n",
       "DMLP  1.354748  1.318924  1.273361  1.339532  1.323696  1.350913  1.310643   \n",
       "NTES  1.409112  1.386497  1.233636  1.354532  1.230854  1.341441  1.258595   \n",
       "EMD   1.368753  1.333343  1.209980  1.292107  1.215383  1.347692  1.306719   \n",
       "QMN   1.346513  1.337603  1.304054  1.345989  1.281007  1.311021  1.273693   \n",
       "EVFM  1.393899  1.385622  1.402563  1.421368  1.381045  1.406295  1.403904   \n",
       "TGTX  1.384723  1.296169  1.242676  1.364260  1.323333  1.295656  1.280871   \n",
       "ATU   1.319998  1.284238  1.028932  1.237310  1.206692  1.249363  1.142608   \n",
       "BTX   1.402912  1.340666  1.214178  1.336390  1.279417  1.274968  1.250312   \n",
       "CYTK  1.347784  1.362697  1.274688  1.354378  1.320663  1.286321  1.303765   \n",
       "TUSA  1.296503  1.266353  0.949941  1.242425  1.147206  1.237573  1.110229   \n",
       "HEWG  1.299288  1.277875  0.815832  1.253726  0.994422  1.215887  1.089368   \n",
       "FRPH  1.348607  1.291971  1.239602  1.313323  1.317865  1.247835  1.251962   \n",
       "ATNM  1.355064  1.337373  1.263846  1.353589  1.352719  1.309088  1.334211   \n",
       "UBFO  1.378311  1.407838  1.308690  1.404994  1.400978  1.390308  1.362360   \n",
       "FIVN  1.464232  1.298061  1.248607  1.353702  1.318298  1.225675  1.207969   \n",
       "PEG   1.320373  1.388747  1.378847  1.261317  1.267486  1.358975  1.356219   \n",
       "KLAC  1.359902  1.297062  1.137704  1.278501  1.261196  1.255603  1.143870   \n",
       "UNT   1.369433  1.317702  1.127092  1.323670  1.272766  1.320302  1.263555   \n",
       "WATT  1.359694  1.396771  1.296411  1.368912  1.340195  1.371638  1.319797   \n",
       "AVGR  1.443166  1.369277  1.364796  1.404079  1.383054  1.356614  1.366163   \n",
       "DEF   1.267071  1.252082  0.948921  1.157007  1.074623  1.174504  1.046542   \n",
       "VIPS  1.382940  1.362381  1.209026  1.310800  1.253726  1.319568  1.276507   \n",
       "CEI   1.397165  1.358246  1.399399  1.383800  1.391132  1.419795  1.387345   \n",
       "FXA   1.387766  1.350728  1.227833  1.274204  1.189893  1.355306  1.273140   \n",
       "UTHR  1.304650  1.273688  1.161793  1.317108  1.315681  1.268911  1.266462   \n",
       "MIK   1.321265  1.302021  1.159114  1.276571  1.254082  1.331459  1.284569   \n",
       "EXK   1.395290  1.396734  1.429208  1.374524  1.350827  1.404960  1.366276   \n",
       "CMA   1.332837  1.275873  0.688861  1.301617  1.151432  1.232582  1.155235   \n",
       "SNOA  1.385213  1.366694  1.337497  1.381839  1.373399  1.408846  1.382782   \n",
       "BOTJ  1.408182  1.427636  1.389511  1.412713  1.393012  1.427814  1.425151   \n",
       "AIR   1.307711  1.276006  1.122179  1.275675  1.266999  1.264514  1.166649   \n",
       "GER   1.333497  1.295933  1.073443  1.304278  1.181531  1.312782  1.237878   \n",
       "DVYE  1.344783  1.282867  0.960038  1.226750  1.038823  1.261004  1.127952   \n",
       "GAM   1.294530  1.276895  0.900669  1.235760  1.094573  1.233158  1.098288   \n",
       "AY    1.371675  1.330058  1.227835  1.313990  1.278115  1.307607  1.289480   \n",
       "LAC   1.404617  1.373751  1.273446  1.391301  1.340728  1.343669  1.321468   \n",
       "NKSH  1.323986  1.290420  1.156971  1.316882  1.305110  1.250867  1.240656   \n",
       "EME   1.329272  1.240923  1.017933  1.225540  1.220275  1.229973  1.092095   \n",
       "BBDO  1.364206  1.331810  1.279042  1.316963  1.307707  1.364871  1.294572   \n",
       "GRIF  1.398417  1.300679  1.308721  1.371067  1.379197  1.359185  1.361314   \n",
       "IMGN  1.381707  1.393739  1.246031  1.387570  1.299652  1.349468  1.294820   \n",
       "\n",
       "          GNUS      RINF      DMLP  ...       GER      DVYE       GAM  \\\n",
       "DF    1.371249  1.392399  1.354748  ...  1.333497  1.344783  1.294530   \n",
       "SQBG  1.351607  1.337602  1.318924  ...  1.295933  1.282867  1.276895   \n",
       "C     1.349763  1.259024  1.273361  ...  1.073443  0.960038  0.900669   \n",
       "PPC   1.380031  1.344272  1.339532  ...  1.304278  1.226750  1.235760   \n",
       "VOD   1.334415  1.347617  1.323696  ...  1.181531  1.038823  1.094573   \n",
       "TRUP  1.417175  1.365208  1.350913  ...  1.312782  1.261004  1.233158   \n",
       "NATI  1.396013  1.359526  1.310643  ...  1.237878  1.127952  1.098288   \n",
       "GNUS  0.000000  1.390259  1.380223  ...  1.304188  1.355924  1.375821   \n",
       "RINF  1.390259  0.000000  1.330342  ...  1.257333  1.293816  1.325931   \n",
       "DMLP  1.380223  1.330342  0.000000  ...  1.109242  1.179203  1.255160   \n",
       "NTES  1.370103  1.374489  1.371129  ...  1.286188  1.096318  1.201492   \n",
       "EMD   1.372539  1.328126  1.261902  ...  1.090142  1.051113  1.096903   \n",
       "QMN   1.340338  1.349149  1.303966  ...  1.239090  1.218023  1.183279   \n",
       "EVFM  1.398399  1.449318  1.391662  ...  1.384900  1.415307  1.393752   \n",
       "TGTX  1.369878  1.346539  1.361311  ...  1.272543  1.232470  1.228533   \n",
       "ATU   1.376660  1.320284  1.204098  ...  1.113167  1.049030  1.051130   \n",
       "BTX   1.396645  1.339611  1.350809  ...  1.256337  1.217687  1.248358   \n",
       "CYTK  1.348820  1.398223  1.359404  ...  1.296619  1.303166  1.250677   \n",
       "TUSA  1.379098  1.263951  1.251722  ...  1.038677  1.006315  0.914362   \n",
       "HEWG  1.363820  1.276640  1.261164  ...  1.123287  0.878540  0.861420   \n",
       "FRPH  1.407373  1.345107  1.350224  ...  1.286932  1.239263  1.232577   \n",
       "ATNM  1.404966  1.356373  1.314840  ...  1.269468  1.306591  1.279425   \n",
       "UBFO  1.362908  1.401274  1.376451  ...  1.383459  1.344418  1.340341   \n",
       "FIVN  1.437157  1.396388  1.329944  ...  1.303536  1.222485  1.176771   \n",
       "PEG   1.365312  1.428680  1.369326  ...  1.323102  1.227926  1.232299   \n",
       "KLAC  1.379136  1.371200  1.314745  ...  1.253279  1.089768  1.063611   \n",
       "UNT   1.366131  1.284826  1.089036  ...  0.907121  1.089415  1.163492   \n",
       "WATT  1.387022  1.392800  1.349881  ...  1.290352  1.293735  1.293815   \n",
       "AVGR  1.414643  1.380487  1.397394  ...  1.383264  1.395972  1.350534   \n",
       "DEF   1.348416  1.290823  1.231411  ...  1.050778  0.857485  0.814193   \n",
       "VIPS  1.327478  1.358731  1.332251  ...  1.259965  1.153060  1.170884   \n",
       "CEI   1.442039  1.377497  1.287617  ...  1.297164  1.374788  1.379642   \n",
       "FXA   1.378786  1.322395  1.255891  ...  1.185864  0.925489  1.171182   \n",
       "UTHR  1.416204  1.347803  1.368342  ...  1.265956  1.216382  1.191592   \n",
       "MIK   1.377741  1.350557  1.313047  ...  1.210862  1.189201  1.173464   \n",
       "EXK   1.369992  1.392945  1.288029  ...  1.269001  1.209598  1.381122   \n",
       "CMA   1.382724  1.279306  1.266121  ...  1.101972  1.033288  1.008746   \n",
       "SNOA  1.414215  1.358307  1.354187  ...  1.309071  1.351609  1.313761   \n",
       "BOTJ  1.394020  1.398294  1.439555  ...  1.373003  1.391792  1.351739   \n",
       "AIR   1.387582  1.283042  1.243795  ...  1.200966  1.129259  1.101129   \n",
       "GER   1.304188  1.257333  1.109242  ...  0.000000  1.032329  1.052108   \n",
       "DVYE  1.355924  1.293816  1.179203  ...  1.032329  0.000000  0.903295   \n",
       "GAM   1.375821  1.325931  1.255160  ...  1.052108  0.903295  0.000000   \n",
       "AY    1.368737  1.311674  1.317009  ...  1.174026  1.180152  1.197497   \n",
       "LAC   1.358605  1.333504  1.340594  ...  1.277929  1.257882  1.307883   \n",
       "NKSH  1.361245  1.347925  1.327500  ...  1.283910  1.232930  1.221497   \n",
       "EME   1.373982  1.301961  1.263586  ...  1.149367  1.090730  1.052477   \n",
       "BBDO  1.428086  1.372779  1.304677  ...  1.289427  1.119280  1.272371   \n",
       "GRIF  1.353817  1.399989  1.420836  ...  1.348020  1.341781  1.321308   \n",
       "IMGN  1.383810  1.366735  1.356056  ...  1.310709  1.278576  1.266978   \n",
       "\n",
       "            AY       LAC      NKSH       EME      BBDO      GRIF      IMGN  \n",
       "DF    1.371675  1.404617  1.323986  1.329272  1.364206  1.398417  1.381707  \n",
       "SQBG  1.330058  1.373751  1.290420  1.240923  1.331810  1.300679  1.393739  \n",
       "C     1.227835  1.273446  1.156971  1.017933  1.279042  1.308721  1.246031  \n",
       "PPC   1.313990  1.391301  1.316882  1.225540  1.316963  1.371067  1.387570  \n",
       "VOD   1.278115  1.340728  1.305110  1.220275  1.307707  1.379197  1.299652  \n",
       "TRUP  1.307607  1.343669  1.250867  1.229973  1.364871  1.359185  1.349468  \n",
       "NATI  1.289480  1.321468  1.240656  1.092095  1.294572  1.361314  1.294820  \n",
       "GNUS  1.368737  1.358605  1.361245  1.373982  1.428086  1.353817  1.383810  \n",
       "RINF  1.311674  1.333504  1.347925  1.301961  1.372779  1.399989  1.366735  \n",
       "DMLP  1.317009  1.340594  1.327500  1.263586  1.304677  1.420836  1.356056  \n",
       "NTES  1.367642  1.338405  1.367372  1.271085  1.318104  1.367840  1.308013  \n",
       "EMD   1.268549  1.307533  1.337209  1.265720  1.302400  1.302839  1.336363  \n",
       "QMN   1.300212  1.351084  1.320796  1.292775  1.323743  1.358299  1.326575  \n",
       "EVFM  1.425014  1.408469  1.435233  1.409413  1.397165  1.400592  1.380650  \n",
       "TGTX  1.301004  1.344109  1.322470  1.271195  1.364288  1.334357  1.229402  \n",
       "ATU   1.265372  1.290888  1.250543  1.019832  1.289292  1.323300  1.305267  \n",
       "BTX   1.301843  1.294707  1.257247  1.219223  1.319059  1.352364  1.248185  \n",
       "CYTK  1.343034  1.333935  1.309249  1.242926  1.367078  1.353540  1.246582  \n",
       "TUSA  1.244969  1.286038  1.204942  1.047031  1.279491  1.327555  1.242779  \n",
       "HEWG  1.231673  1.247657  1.167146  1.018174  1.297795  1.337125  1.271439  \n",
       "FRPH  1.319569  1.292344  1.201767  1.180724  1.327646  1.344212  1.347646  \n",
       "ATNM  1.328110  1.317426  1.378737  1.319331  1.384536  1.371974  1.380466  \n",
       "UBFO  1.369436  1.391311  1.317584  1.331553  1.345847  1.346490  1.388588  \n",
       "FIVN  1.311836  1.356844  1.310764  1.228180  1.353134  1.353271  1.304764  \n",
       "PEG   1.266765  1.388160  1.384641  1.356602  1.346793  1.405866  1.416668  \n",
       "KLAC  1.325954  1.323176  1.276865  1.139725  1.342795  1.402007  1.260199  \n",
       "UNT   1.217185  1.270017  1.300368  1.183553  1.292154  1.329287  1.325829  \n",
       "WATT  1.371988  1.335237  1.334762  1.308182  1.349115  1.381351  1.326337  \n",
       "AVGR  1.412277  1.408626  1.327002  1.365276  1.407702  1.385942  1.363035  \n",
       "DEF   1.208836  1.271688  1.196474  0.996561  1.256252  1.353476  1.276384  \n",
       "VIPS  1.345273  1.333617  1.357565  1.231608  1.343160  1.380370  1.287995  \n",
       "CEI   1.368899  1.395356  1.407034  1.374451  1.405262  1.391169  1.394595  \n",
       "FXA   1.299141  1.296048  1.336467  1.255711  1.248522  1.418927  1.347640  \n",
       "UTHR  1.306129  1.335621  1.310933  1.193863  1.360814  1.340775  1.251992  \n",
       "MIK   1.271032  1.309429  1.343538  1.199440  1.342858  1.362791  1.281701  \n",
       "EXK   1.330131  1.344728  1.367117  1.397794  1.315376  1.380026  1.394986  \n",
       "CMA   1.260562  1.287847  1.153965  1.035311  1.301888  1.296308  1.301105  \n",
       "SNOA  1.351513  1.406980  1.367426  1.370183  1.366142  1.393962  1.400319  \n",
       "BOTJ  1.387541  1.427367  1.392962  1.399766  1.421393  1.380470  1.416221  \n",
       "AIR   1.268694  1.312998  1.207332  1.071365  1.287874  1.343606  1.294727  \n",
       "GER   1.174026  1.277929  1.283910  1.149367  1.289427  1.348020  1.310709  \n",
       "DVYE  1.180152  1.257882  1.232930  1.090730  1.119280  1.341781  1.278576  \n",
       "GAM   1.197497  1.307883  1.221497  1.052477  1.272371  1.321308  1.266978  \n",
       "AY    0.000000  1.301453  1.313603  1.299288  1.337452  1.337526  1.334861  \n",
       "LAC   1.301453  0.000000  1.339819  1.333644  1.377260  1.371110  1.361430  \n",
       "NKSH  1.313603  1.339819  0.000000  1.181479  1.322576  1.346102  1.335597  \n",
       "EME   1.299288  1.333644  1.181479  0.000000  1.296549  1.349177  1.307865  \n",
       "BBDO  1.337452  1.377260  1.322576  1.296549  0.000000  1.387160  1.378682  \n",
       "GRIF  1.337526  1.371110  1.346102  1.349177  1.387160  0.000000  1.398521  \n",
       "IMGN  1.334861  1.361430  1.335597  1.307865  1.378682  1.398521  0.000000  \n",
       "\n",
       "[50 rows x 50 columns]"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dist = np.sqrt( 2*(1 - corr) ) #distance dataframe \n",
    "dist"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Taking the Minimum Spanning Tree of Asset Distance\n",
    "Kruskal's Algorithm was used with a DFS component for connection checking."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>DF</th>\n",
       "      <th>SQBG</th>\n",
       "      <th>C</th>\n",
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       "      <th>IMGN</th>\n",
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       "      <th>SQBG</th>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.240923</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PPC</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VOD</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TRUP</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NATI</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GNUS</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.304188</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RINF</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.257333</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DMLP</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NTES</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.096318</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EMD</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.051113</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>QMN</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EVFM</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TGTX</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.229402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ATU</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BTX</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CYTK</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TUSA</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.914362</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HEWG</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.815832</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.994422</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.247657</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FRPH</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ATNM</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UBFO</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.308690</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FIVN</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.176771</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PEG</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KLAC</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UNT</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.089036</td>\n",
       "      <td>...</td>\n",
       "      <td>0.907121</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WATT</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AVGR</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.327002</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DEF</th>\n",
       "      <td>1.267071</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.157007</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.174504</td>\n",
       "      <td>1.046542</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.857485</td>\n",
       "      <td>0.814193</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.996561</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VIPS</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CEI</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.287617</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FXA</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.925489</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UTHR</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.161793</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIK</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EXK</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CMA</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.688861</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.153965</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.296308</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SNOA</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.309071</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BOTJ</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AIR</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GER</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.304188</td>\n",
       "      <td>1.257333</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.032329</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.174026</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DVYE</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.032329</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.11928</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GAM</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AY</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.174026</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LAC</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NKSH</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EME</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.240923</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BBDO</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.119280</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GRIF</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IMGN</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>50 rows × 50 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            DF      SQBG         C       PPC       VOD      TRUP      NATI  \\\n",
       "DF    0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "SQBG  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "C     0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "PPC   0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "VOD   0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "TRUP  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "NATI  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "GNUS  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "RINF  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "DMLP  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "NTES  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "EMD   0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "QMN   0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "EVFM  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "TGTX  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "ATU   0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "BTX   0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "CYTK  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "TUSA  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "HEWG  0.000000  0.000000  0.815832  0.000000  0.994422  0.000000  0.000000   \n",
       "FRPH  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "ATNM  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "UBFO  0.000000  0.000000  1.308690  0.000000  0.000000  0.000000  0.000000   \n",
       "FIVN  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "PEG   0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "KLAC  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "UNT   0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "WATT  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "AVGR  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "DEF   1.267071  0.000000  0.000000  1.157007  0.000000  1.174504  1.046542   \n",
       "VIPS  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "CEI   0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "FXA   0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "UTHR  0.000000  0.000000  1.161793  0.000000  0.000000  0.000000  0.000000   \n",
       "MIK   0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "EXK   0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "CMA   0.000000  0.000000  0.688861  0.000000  0.000000  0.000000  0.000000   \n",
       "SNOA  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "BOTJ  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "AIR   0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "GER   0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "DVYE  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "GAM   0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "AY    0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "LAC   0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "NKSH  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "EME   0.000000  1.240923  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "BBDO  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "GRIF  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "IMGN  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
       "\n",
       "          GNUS      RINF      DMLP  ...       GER      DVYE       GAM  \\\n",
       "DF    0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "SQBG  0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "C     0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "PPC   0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "VOD   0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "TRUP  0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "NATI  0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "GNUS  0.000000  0.000000  0.000000  ...  1.304188  0.000000  0.000000   \n",
       "RINF  0.000000  0.000000  0.000000  ...  1.257333  0.000000  0.000000   \n",
       "DMLP  0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "NTES  0.000000  0.000000  0.000000  ...  0.000000  1.096318  0.000000   \n",
       "EMD   0.000000  0.000000  0.000000  ...  0.000000  1.051113  0.000000   \n",
       "QMN   0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "EVFM  0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "TGTX  0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "ATU   0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "BTX   0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "CYTK  0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "TUSA  0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.914362   \n",
       "HEWG  0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "FRPH  0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "ATNM  0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "UBFO  0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "FIVN  0.000000  0.000000  0.000000  ...  0.000000  0.000000  1.176771   \n",
       "PEG   0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "KLAC  0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "UNT   0.000000  0.000000  1.089036  ...  0.907121  0.000000  0.000000   \n",
       "WATT  0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "AVGR  0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "DEF   0.000000  0.000000  0.000000  ...  0.000000  0.857485  0.814193   \n",
       "VIPS  0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "CEI   0.000000  0.000000  1.287617  ...  0.000000  0.000000  0.000000   \n",
       "FXA   0.000000  0.000000  0.000000  ...  0.000000  0.925489  0.000000   \n",
       "UTHR  0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "MIK   0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "EXK   0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "CMA   0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "SNOA  0.000000  0.000000  0.000000  ...  1.309071  0.000000  0.000000   \n",
       "BOTJ  0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "AIR   0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "GER   1.304188  1.257333  0.000000  ...  0.000000  1.032329  0.000000   \n",
       "DVYE  0.000000  0.000000  0.000000  ...  1.032329  0.000000  0.000000   \n",
       "GAM   0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "AY    0.000000  0.000000  0.000000  ...  1.174026  0.000000  0.000000   \n",
       "LAC   0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "NKSH  0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "EME   0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "BBDO  0.000000  0.000000  0.000000  ...  0.000000  1.119280  0.000000   \n",
       "GRIF  0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "IMGN  0.000000  0.000000  0.000000  ...  0.000000  0.000000  0.000000   \n",
       "\n",
       "            AY       LAC      NKSH       EME     BBDO      GRIF      IMGN  \n",
       "DF    0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "SQBG  0.000000  0.000000  0.000000  1.240923  0.00000  0.000000  0.000000  \n",
       "C     0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "PPC   0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "VOD   0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "TRUP  0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "NATI  0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "GNUS  0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "RINF  0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "DMLP  0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "NTES  0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "EMD   0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "QMN   0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "EVFM  0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "TGTX  0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  1.229402  \n",
       "ATU   0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "BTX   0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "CYTK  0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "TUSA  0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "HEWG  0.000000  1.247657  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "FRPH  0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "ATNM  0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "UBFO  0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "FIVN  0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "PEG   0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "KLAC  0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "UNT   0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "WATT  0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "AVGR  0.000000  0.000000  1.327002  0.000000  0.00000  0.000000  0.000000  \n",
       "DEF   0.000000  0.000000  0.000000  0.996561  0.00000  0.000000  0.000000  \n",
       "VIPS  0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "CEI   0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "FXA   0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "UTHR  0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "MIK   0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "EXK   0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "CMA   0.000000  0.000000  1.153965  0.000000  0.00000  1.296308  0.000000  \n",
       "SNOA  0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "BOTJ  0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "AIR   0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "GER   1.174026  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "DVYE  0.000000  0.000000  0.000000  0.000000  1.11928  0.000000  0.000000  \n",
       "GAM   0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "AY    0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "LAC   0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "NKSH  0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "EME   0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "BBDO  0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "GRIF  0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "IMGN  0.000000  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
       "\n",
       "[50 rows x 50 columns]"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mst_50 = mst(dist)\n",
    "mst_50"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### NX for Visualization\n",
    "\n",
    "#### Original Distance Graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "import networkx as nx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels = {v: k for v, k in enumerate( dist.index.tolist() )}\n",
    "\n",
    "#visualizing our original distance graph\n",
    "d_graph = nx.from_numpy_array(np.array(dist))\n",
    "d_pos = nx.spring_layout(d_graph)\n",
    "nx.draw(d_graph, d_pos)\n",
    "_ = nx.draw_networkx_labels(d_graph, d_pos, labels, font_size=8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Visualizing NX's Kruskal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#using nx to compute MST\n",
    "d_mst = nx.minimum_spanning_tree(d_graph)\n",
    "mst_pos = nx.spring_layout(d_mst)\n",
    "nx.draw(d_mst, mst_pos)\n",
    "_ = nx.draw_networkx_labels(d_mst, mst_pos, labels, font_size=8)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Visualizing my MST"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "my_mst = nx.from_numpy_array(np.array(mst_50)) \n",
    "my_pos = nx.spring_layout(my_mst)\n",
    "nx.draw(my_mst, my_pos)\n",
    "_ = nx.draw_networkx_labels(my_mst, my_pos, labels, font_size=8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can visually ascertain that our MST's are isomorhpic, we will go ahead and check this numerically."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "check_mst(dist, mst_50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualizing the Hierarchical Nature of Asset Distance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Grind\\Anaconda3\\envs\\ht\\lib\\site-packages\\seaborn\\matrix.py:595: ClusterWarning: scipy.cluster: The symmetric non-negative hollow observation matrix looks suspiciously like an uncondensed distance matrix\n",
      "  metric=self.metric)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 504x504 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(7, 7))\n",
    "dist_map = sns.clustermap(dist)\n",
    "dist_map.fig.suptitle('Distance Matrix of Log Returns', fontsize = 20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusion\n",
    "\n",
    "This imlpementation of the minimum spanning tree makes use of depth first search to indentify if a node is connected, which is the most computationally intensive part of Kruskal's Algorithm. This was chosen as opposed to breadth first search (or the consecutive powering of the adjacency matrices at O{n^3} ) to identify all possible paths between two nodes. By using DFS, we maintain a time complexity of O(N^2), however our opeartions are using DataFrame objects and making minimal use of the well-optimized numpy and scipy functions. All DataFrame operations are derived from first principles programming."
   ]
  }
 ],
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